Tableau Training for Beginners | Tableau Tutorial | Intellipaat


Hey guys, welcome to Intellipaat. Today’s
session is on Tableau. Tableau is one of the most powerful business intelligence tool
being deployed by most of the organization to find insightful
information from their data. Keeping this in mind, we have come up with a very
comprehensive tutorial on tableau. So let’s look at the agenda for today’s
session. We will start with introduction to tableau. Then we will discuss how you
can install tableau desktop. Going further, we will look at tableau
architecture and learn how to use dimensions and measures in tableau.
Moving further, we will look at various file types in tableau and we will learn
about how you can use data joining and data blending in tableau and at last we
will look at various filters available in tableau. So let’s get started.
Basically, these tableau products are divided into two types first is the
developer tools and the second one is the sharing tools. So now developer tools is nothing but they are used to create the dashboards,
the worksheets, basically your visualizations. So with the help of this
developer tools, you create your visualizations and with the help of the
sharing tools the visualizations that you’ve created using your developer
tools are shared to audiences right. I hope I’m being clear
developer tools and sharing tools. So we have tableau desktop as the main
developing tool okay and we have tableau public as well right. So tableau desktop,
we have two editions we have personal and professional edition okay. All your
development work are done right here in your tableau desktop. You create your
reports, you create your charts and all the analysis process is done in your
tableau desktop right. And when it comes to tableau public, it serves I mean it is
used for both the development and sharing purpose right. You can develop
your charts, your reports using tableau public as well ok. It is a free
product offered by the tableau company but there is a limitation when it
comes to tableau public, you can connect it only to a limited file types in which
your data source must be right and there’s no security when it comes to
tableau public, everyone can see your data when you publish your dashboard in
tableau public ok. So this is about tableau public right and then we have
the sharing tools ok. Sharing tools, they use the developer tools in order to
develop your visualizations and then they share your visualizations to the
audiences ok. We have tableau online and tableau server okay. I think tableau
online is not mentioned over here but we have tableau online and tableau server.
We have two sharing tools ok. But one limitation both I mean with the
help of both tableau online and tableau server, you can publish your data but the
limitation of tableau online is that you know editing of workbooks or any editing
works are limited to the number of rows and your server data connections is
required when it comes to tableau online right. So tableau online is also a
sharing tool but there is one limitation which is nothing but editing of
worksheets inside your tableau online is limited to the number of rows okay and
you only if you need to have a server data connection in tableau online.
But on the other hand, when it comes to tableau server it is also a sharing tool
okay. It is used to share and create visualizations for organizations especially right. So now, why do organizations use tableau server.
They can also use tableau public when it comes to publishing data but when it
comes to organizations they need secure. Yes and tableau server is the sharing
tool which is used by all the organizations because it comes with full
security like the data of an organization is need to be secure right.
So for that purpose tableau server is used as a sharing tool. So you can share
your visualization, you can share your dashboard throughout your particular
organization right. You can decide to whom this particular visualization is to
be shared whether you need to share only the visualization or you need to share
the visualization with the data to which particular member of the organization
and so on. So you can decide on that point when it comes to tableau server
right. So tableau server is fully secure okay when it comes to your data okay. So
you need to use your tableau desktop first to create your visualization and
after that you will have to connect to your tableau server. Your tableau server
will have a user ID and password which is provided by the organization for
security reasons and then after which you can publish your data into tableau
server and you can decide who need who must view the data let’s say your higher
officials your colleagues, you should decide who should view the data along
I mean who should view the visualization and the dashboards that you’ve created
and who shouldn’t or who should view it along with the data and so on okay.
Everything can be decided in your tableau server for the security reasons
okay. So that’s why organizations prefer tableau server when it comes to
publishing the analysis right and we have something called tableau reader. So
during the early days, so tableau reader was the only way for content creators to
share the dashboard right. We didn’t have tableau online or server or to share the
visualizations that was created okay. So they used to build visualizations using
the tableau desktop okay and they used to share those visualizations using
the tableau reader okay and you can share the visualizations using the
tableau reader throughout the organization without access to the
desktop. So when people in your organization do not have access to
the desktop, so when I say they do not have access to the desktop
it means they aren’t supposed to have the access to the data itself right. So
in such cases such audiences will be provided with the visualizations using
this tableau reader right. So early days this was the only sharing tool which was
available right and we have something called tableau prep as well.
So tableau prep is one of the latest products launched by the tableau company
okay. It’s the tableau’s, you can say it’s the ETL tool, it’s the extract, transform
and load tool of tableau, okay. So tableau prep, it just
prepares your data okay. It’s a personal data preparation tool I can call it a
personal data preparation tool okay. It just allows the users you can aggregate,
you can cleanse, you can merge different rows if you need them in different
columns or otherwise you can you know prepare the data for analysis and
tableau right. You need, you will have some basic things that can be that need to be done to your data and you need those
options to be used during every analysis. Let’s say, you will need to split a
particular column into two or you will need to merge two columns into one and
you need this merge to be there in all your analysis in all your I mean every
time you open your tableau, you connect your tableau with your data source you need this merge merged column to be there
always. You needn’t go every time and keep merging or keep splitting so this
is just an example okay. So this tableau prep okay it prepares the data by
which every time you will be given the prepared data for analysis, you needn’t
start from the scratch right. I hope you understood about tableau prep as well
okay. So these are the different products offered by the tableau company okay and
so now this is a start page of tableau. We are going to connect our tableau with
the sample superstore data which was provided by the tableau company itself
during the downloading process right. So it is a Microsoft Excel file, so I’ll
just click on this by where after which I will be able to view all the excel
files available okay. I’ll click on the sample superstore
and I’ll say open. So as you can see my sample superstore,
the name of my data source is visible over here okay. This is my data source
page right here okay. The connection, it gives me the information about the which
data source I am connected to, the name of my data source, the file
type to which my data source belongs to okay and you have the different sheets
available we have three sheets. So as you can see in my excel file over here we
have three sheets orders people and returns okay we have three sheets
available and similarly you can see three different sheets over here and
these are nothing but the named ranges of these three sheets so in excel
whenever you create a sheet a named range is automatically created okay so
it it is you know just the same it is just a copy of your actual sheet okay
and you there’s just this one small change between your sheet and your name
range right your table or your sheet it’s it’s a defined grid of you know
cells of data right and your named range it is just one or more cells to which
you have assigned a particular name right so I’ll just give you a very
simple example okay just one point by which you will understand why what is
the actual sheet and what is the named range all about right so for example if
I have a column in my any one of my sheet any one of my actual sheet and
that is nothing but the sum of two different columns let’s say column a1
and b1 or let’s say any two columns right so the column header will be a1
plus b1 right so when I go into my named range right the header will be changed
will be given a name it will be assigned a name as let’s say income plus expenses
or whatever your a 1 and a 2 is supposed to be right so that is a very small
difference between your actual sheet you’re named range but other than this
you will not be I don’t think there’s any difference when it comes to sheets
and named range you can use both these to perform the analysis and tableau
right it will work just the same right so now we’ll be using the different
sheets over here okay and before that let me tell you about this data
interpreter which is available over here now what is this data interpreter so
data interpreter it just cleans your data it helps to clean your teeth this
we have connected our data source okay and you have something called data
interpreter over here so data interpreter it helps to clean your data
right what do you mean by cleaning your data right so when we create a sheet for
to make it user friendly we have some titles we have some stack headers we may
have some notes okay we may have some empty cells empty rows or columns in
order to add a white space and so on we might have all these footers and headers
in our data right so when we use this data interpreter it helps to remove all
those it detects all these types of extra fittings okay which aren’t needed
for the analysis purpose it bypasses all these items and it identifies the actual
data with which you will be analyzing you after connecting with tableau right
so this data interpreter comes only when you connect it with an excel file a
comma separated file a PDF file and Google sheets write this data
interpreter works only for these types of files so if you connect it with some
other type of file you won’t be able to view this data interpreter okay so yes
and now this is known as the canvas over here you will drag your sheets over here
so let me drag my fur sheet okay said mama so now I have my
order sheet over here and all the different columns and rows which are
present in my order sheet will be visible right here okay and I all I have
to do is just drag a particular sheet and drop it in my canvas area okay and
then I’ll have to jump to my sheet it says go to work sheet over here where I
will be building my visualizations right but before that let me I mean let us
just discuss about the different sorting options which are
available over here okay and after which I will be explaining about this over
here we have two different ways by which you can connect your data source with
tableau the first one is the live connection and the second one is an
extract connection okay right now by default it is always a live connection
okay so now we have been connected with our data source sample superstore in a
live manner right so I’ll just tell you all the basic formatting options over
here sorting and formatting options after which and explain about these two
the differences between these two ways of connections okay so as you can see
you have this sorting order so right now it is in the data source order okay you
can either change it to A to Z ascending right when I click on a Stew’s it is
sending all my column headers the column names they will be sorted out in an A to
Z descending order right so I have only one sheet over here and the columns of
this particular sheet are sorted in this A to Z order okay you have Z to a
descending and you have something called A to Z ascending per table and Z to a
descending per table so now why does this per table come over here okay so at
one point of time I can have a maximum of 32 tables in my canvas okay so we
have this join joining process which is which can be performed let me have my
second sheet okay so as you can see there’s a inner join which has been
created between the two sheets okay we have four different types of joins we
which we can change it manually okay we’ll be discussing about this data
joining and data blending soon in our upcoming sessions okay
so right now we have two tables or two sheets in our canvas
okay and by default and inner join is applied right so now when I choose a to
Z ascending / table okay so first I’ll have my the columns
of my first sheet orders okay and as you can see you have the sheet name right on
top of the column name which indicates to which sheet this particular column
belongs to right so as you can see after this you have the people table and you
have the people table again sorted from A to Z right so it is a to z per table
or Z to a per table similarly if I say A to Z is sending okay the columns of both
the tables get mixed up in order to arrange it in an A to Z descending order
as you can see I have a product profit quantity which belongs to my orders
table and after which I have region which belongs to the people table and
again orders orders and so on this is because it is not a 2z descending per
table it is common opposite ascending right and as you can see you have to
region columns over here one is normal region and the other one is a region
with people inside braces so what does this this signify this tells us that
when you want to create a join you will need to have a common column a common
field by which a join can be established right so this tells me that the region
of people is the field common I mean the region is the field which is common
between both both these sheets right so this tells me the field which has been
used in order to perform a join right so this is just the
so we have something called managed metadata over sure so when you click on
that we have the different field names which are available inside my orders
table okay the table name is given right over
here and we have something called remote fields name so now what does this remote
field name stand for so when I go back to my this page over
here when I click on this preview data source over here I can rename a column
right here in tableau so no change is going to be made in my data source but
just for analysis purpose just for my you know way of let’s say how my how I
should you know understand this particular column as I would like to
rename this you know make it a short form of it I needn’t I don’t want such a
big column name for example customer name I wanted to be as CN I don’t want I
I want to make it shot it might be any season so I would I can very well rename
the column okay right here in tableau there’s no change going to may be made
inside my actual data right so I can just double click on this option over
here and I can rename it okay or I can click on this drop-down arrow and I have
this rename option over here I can use that as well so let me rename it as C n
okay customer name okay C and now the column has been renamed okay
so again when I click on this drop-down option I can reset it to the name it
originally had right as you can see we have the customer name over here so now
let me rename it as C n right and now when I go into this managed metadata so
as you can see the field name it displays the field names inside tableau
right so C n I had renamed my customer name to C n but though I have
made a change only the field name displays the change but the remote field
name it does it gives the original name as it is available in the data source so
with this you know you can understand that field names are nothing but the
names of the fields inside tableau while working with tableau but the remote
field name it is the actual name of any particular field as it is available in
your data source right so this is the difference between field name and remote
field name so at any point of time if you have renamed your fields and you
would like to view the original name of that particular field you can use this
remote field name option I mean this column to just you know go through that
right so we’ll go back to it and I’ll reset the name of this okay
and then we can we have different file types available in tableau and as you
can see you have something called ABC over here you have a globe symbol over
here and you have a hash symbol over here you have a calendar symbol and so
on we have so just click on that small symbol which is visible and you can see
these are the different data types which are available in tableau okay so this is
a string data type we have boolean or sOooo false values we have dead
we have date and time we have number hole and number decimal and we have
something called geographical roll so JA graphical roll is nothing but it might
be a country it might be a state okay it might be a city we also have airports
which can be you know linked with the help of the latitude and longitude we
have built in latitude and longitude okay which can be assigned as a
geographical roll data type so geographical roll data type is used
while creating maps right so we’ll just go through all those things as well so
basically these are the different types data types which are available with
tableau so number as a decimal and whole we have data and time date string
boolean and geographical rule okay so this small symbol over here indicates
which data type this particular column belongs to okay yes
so and we can also find out the number of you know rows in this particular
sheet so right now thousand rows are visible
if I would like to say I need only the only the five rows only fire rows will
be visible and similarly if I want to find out let’s say the 20,000 rows
you so as you can see 20,000 is something is
a number which was greater and the actual number of rows available in my
sheet so when I specify a number which is greater than my you know actual size
itself it will automatically be converted to the original size so when
you click on this view data over here right next to my sheet name you will be
able to see the entire data the total number of rows and all the different
columns which are available in this particular sheet right and you can very
well hide and unhide a few fields you would like to hide a few fields while
the analysis purpose right you can very well do that with the help of let’s say
this drop-down over here you can just click on hide okay
so customer ID is being hidden from my view okay so I can just click on this
show hidden fields okay after which the field which was hidden will be grayed
out okay and I can very well unhide it again in a similar manner okay
and we have an option to split as well okay let me say okay I have my okay I have my customer
ID okay first I’ll go I’ll have my country okay so when I just just for an
example purpose okay I don’t want to split my country as in real time as in a
real use case scenario so just this is just for explanation purpose okay so
when I go into split okay so it will ask the separator by which I in McCallum
needs to be split okay so I can mention the separator as – or comma semicolon :
and so on okay and it will ask whether you need to
split the first half for the last half or split all right and the number of
columns which you need to create as and you want to place those splits in and so
on okay I’ll just just let’s say you can also split the product name okay
you have the split option and as you can see product name has pain okay I don’t
think product name is okay it’s not split let’s see country okay so you can
just spell let’s say column I mean customer ID you can just split it use
the custom split and I’ll have to mention either it’s a hyphen or a comma
and you know the the separator the leaves the delimiter I have to mention
it after which I can separate either the first half or the last half okay so this
is the basic splitting option if you need you can use these options inside
your analysis okay so after going into the sheet okay see these are the
different splits that were created automatically with the help of the space
as my split up yes I didn’t know though I had not
mention anything in my product name split I did not mention a delimiter it
has considered the space as the automatic delimiter and it has been
split into these many number of columns right
in these cases space has been chosen as the default split limiter and in
customer ID – as has been chosen as the delimiter if I want to mention anything
else as comma colon and so on I can mention it which will then be used as
the split all right so yes this is the basics about column formatting and
sorting okay now we’ll be discussing about these two options over here the
life and extract connections right okay so now as I told you we’ll be discussing
about the life and extract connections different the difference is between live
and extract connection so first let me theoretically tell you what both mean
right so when I only when I place any particular sheet over here those options
are visible okay I have a live or extract I can toggle between both okay
one at any particular time I can either have a live connection or an extract
connection so as the name tells me live connection is nothing but my Tablo is
connected to my data source in a live manner in the sense there is always a
connection between the data source and the Tablo right your data might be in
any in in any type of file it might be in any cloud so when I say connect it in
a live manner there is always a connection which is established between
Tablo and my data source okay so one limitation or one
you know who I mean problem which arises when we work with live connection is
that the analysis speed or the way you are working with tableau the process
speed might be affected when your data source is too large right there might be
a few lags a few delay while analysis of being performed or when you are creating
visualizations right here in tableau but one advantage when you have a live
connection as that okay when you try to refresh okay your live connection
whatever changes that have been that have been made in your you know
datasource which it will be updated right children tab you okay but this
refreshing process can also be done when you have an extract connection but you
need an internet connection to perform the refresh when it comes to extract
right so I’ll as just explained once more when you have a live connection you
need only when you have an internet connection established life is possible
right because you are going to connected all the way to your cloud or your server
or your database right so you need internet connection which is established
to have a live connection with your data source okay in such a case while working
with the data that you have right now you can just click on the refresh button
okay after which your entire data here in tableau will be replaced by the data
which might have updates that has been done or during the course of time after
which you have established the initial connection right only when you click on
the extract I mean only on the refresh button your data will get updated as per
the changes made in your actual data source okay but when you choose an
extract connection what happens is a snapshot of your data of your original
data okay a snapshot of your original data will be saved right here in your
system in the tableau repository okay so the processing speed is much faster
because your so your data is right here in your system okay every time you
needn’t go all the way to your cloud fetch data and perform the analysis okay
when you have the extract you do not have the data but you have the snapshot
of your data right here in your system so when do we use these this extract
connection so when you know this extract connection can be useful for example
when you want to increase the speed in which you
are performing the analysis and you have a very large set of data and when you
establish a live connection now the analysis speed might be affected so in
such cases you can switch over to the extract connection on the other hand if
you are traveling when you do not have an internet connection you can very well
extract you know get an extract or snapshot of your original data and after
which you can keep on working keep on analyzing your data while traveling when
you are in an airplane mode or when you do not have an internet connection you
can very well use the extract which will be saved right here in your desktop
right so and you can also extra fresh your extract connection but only after
you you have an internet connection established the particular update made
in your data source will be reflected right here in your tableau right so
these these are the two basic I mean these are the two
I mean these are the information about these two options available okay I hope
you’ve theoretically understood what are the pros and cons of each right so now
let me I have a very small excel file as an example by which these features
basically so now I will connect change the data source over here so now I can
also connect you know multiple data sources to my table one might be an
excel file one might be some other file I can have two or more data sources at
one point of time in tableau and perform the analysis okay that is the concept of
data blending okay we will be discussing that with example as well so right now
let me first change the connection so I am going to click on this drop-down
arrow okay I can edit the connection right I’m going to edit the connection I
am going to connect this live versus extract sample a very simple file to my
tableau now okay so if by doing this my sample store will be removed okay and my
life versus extract will be placed over here okay
so I’ll just show you okay this is that excel file my sample to explain about
life versus extract it’s a very small file it has a few names the states to
which these particular users belong to the date of sale sales that has been
done and the corresponding sales okay it’s just for an explanation perp is
just an example file okay so right now this is my data okay and I’m going to
perform analysis on this data right so I have connected this excel file with my
tableau I have only one sheet and that sheet is visible right over here right
so let me say datasource order okay so whichever order as you can see yes
whichever order it is visible in my data source okay the same thing is is the
same order is being visible right here in my tableau okay so now I’ll go to my
sheet okay so since I try to edit the
connection the splits that I made in my previous example of my previous
datasource remain over here as they do not belong to my data source itself it
belongs only to tableau so it remains right over here so I’ll just delete all
these things so this red exclamatory mark over here tells me that this
particular you know feel did not belong to this
data source right okay so now as you can see I have date name state and sales
which was available in my data source okay and explain what are these
dimensions and measures all about first we’ll discuss about the connections the
two types of connections okay so now I have my name as I’m just dragging the
name and dropping it in my view or in my rules you can use any one method okay
I’ll have my date right and I’ll have my sales okay yes so now I have the information
just as it is in my data source now I’ll go back to my data source I am going to
add another name over here let’s see Shruthi who belongs to let’s say Andhra
Pradesh okay and the purchase has been made on all the particular sales has
been done on let’s say 5th of May 2019 and some let’s say 40 just a random
sales okay so I have added a new row in my data source right and I’m going to
save it okay so now when I go into tableau
okay so my new field then my new row has still not been reflected the changes
that I have made to my data source has not been reflected over here so now how
to find the change how to find okay I’ll go to my data source place as you can
see we are connected with you like okay yes so we are connected analyze nano
wait and now refresh this right so now how do
I bring the changes here okay all of this this one I did name I’ll just click
over here yeah is this refresh here when i refresh my soup okay so now as you can
see the row that I had added in my data source is being reflected in my data
here in tableau okay so just right click on your data source choose this refresh
button okay after wish after which the updates will be reflected right here in
your a block right so this is with the help of the live connection and
this is what happens in a live connection so how do you refresh a live
connection just right-click and choose this refresh button okay now let’s see
what happens in our extract connection so if I want to choose
my datasource to be connected in an extract manner just click on this
extract so as it says extract will include all the data so right now what
are the different fields which are available all the
necessary columns and rows which are available in my data will be included in
the extract so when I try so my new field is right now added inside the data
as well okay so which means this field is also included in the extract which
has been created so now when I try to go to my sheet in order to perform my
analysis it will ask me so now sheet one life versus extract sample so save
extract as so this is going to be saved as a tableau data extract in my tableau
repository right so I’ll say save okay right so now my extract has been
saved right here in my system okay so right now I do not need my
internet connection in order to work in order to analyze my data source okay
so similarly we have everything just as the same but you will notice one small
change between will indicate that you are connected in an extract manner okay
so I’ll just show you see I did not show you when we were in a live connection so
while we are connected in an extract manner you will see two cylinders over
here so one indicates the actual data source and the second cylinder indicates
the extract which is saved right here in your system right so right now so as I
was telling you we have two cylinders over here okay which tells me that we
have been connected to our data source in an extract manner okay so now I am
going back to my data source okay and I’m going to add another name say from
some state and the sales has been made on 10th May 2019 okay and let the sales
be some random number okay so now I have added another row in my data source I am
going to save it okay and after which I move into my tableau so now again I
would like to refresh the data inside tableau I’m
right-clicking on a time and I’m clicking on refresh right as you can see my field that I had
added right over here my last row is still not being reflected inside my
table though I had made a refresh right this is not being reflected in my table
now why is that because this refresh button works only for a live connection
so since we are connected in an extract manner I will have to go into this
extract which is available over here and then
click on refresh ok so as you can see the entire content of
the extract will be replaced during the extract refresh right if you have
modified filters or hidden fields lost during the app so when you try to
refresh as I told you in an extract manner the entire extract will be
replaced with a new snapshot of your new data source right now after we went into
this extract and then try to refresh it we have this column I mean this row
which I had added in my data source so I hope you understood you know what
basically the basic differences between your live and attract connection the
pros and cons right so you can just store like connection again okay and
this tells me extract includes all data till this point of time so this is this
is when I had X are refreshed last okay so till this point of time your extract
will include all the data which was available in your data so still this
point of time okay so after this point of time if I had made any changes in my
data source only after refreshing the extract that particular change will be
updated in my tableau okay and you might ask me a question when we have tableau
server or when people are publishing – boats in the tableau public itself okay
so when changes are being made in their data source or when we have an
organization every minute there might be addition of rows there might be changes
that is being made in a data source so how do we perform this refresh during
such you know cases so in a tableau online and tableau server which is a
sharing tool we have options okay we have scheduled extra refresh options you
can refresh your data automatically you can set a timer let’s say I want my data
to be refreshed every 5 a.m. once a day or every 2 us once
I want my data extract to be refreshed or I want my data to be refreshed
you can assign such scheduled extracts extract refreshes
you have such options in tableau online as well as tableau server okay you
needn’t every time manually go and refresh your extract when you assign
such a schedule extract automatically your data gets updated and as your data
gets updated your analysis you know it gets better because you have automatic
extract refreshes that is being made right so
yes so this is about extract let me just move again back to my life connection
and I’ll go into my sheet now now as you can see you have only one cylinder over
here right I hope you remember when we were in our extract connection we had
two cylinders one is the one indicates the original data and the second one
indicates the snapshot and similarly in a live manner we have only one cylinder
so with this small difference you can identify in which way in which manner
your data source is being connected with tableau either it is in a live manner or
in an extract manner right so I hope you understood the differences the pros and
cons between a live and an extract connection okay it again purely depends
on your requirement on your usage on your files type I mean your file size
whichever way you want your data to be connected with right so while if you’re
just going to use tableau just the practicing purpose right here with our
sample super-slow it doesn’t matter you can either have a live connection or an
extract connection that is in no way going to affect your analysis analysis
in work right okay so now again we’ll go back to our data source I will remove
the sheet from the canvas and I am going to edit the connection I’ll go back to
my sample superstore right see it just clicks away and as you can see we had
these feelings and names in our view when we were discussing about the live
and extract sample right that is why we have these red exclamatory MUX so I’ll
just have my order sheet and I’ll go back here and I’ll just remove them from
the view or I can delete them from here right okay so now we are back with our
sample super stow data okay so now as you can see again we are in a live
manner we have connected it in a live manner we have okay the data source name
has still hasn’t been changed right so it sometimes happens when we try to edit
the connection over here so though we have a data source over here named a new
data source over here the change sometimes might take some time or after
a few you know after you start working for some time it might I mean it will
automatically change so right now let me just come back okay so right now I’m going to connect it to
a Microsoft Excel file sample superstore yes okay
yes so we have however sample superstore over here okay and as
you can see I’ll just show this is the PPD the slides that we have been
provided you will have it in your portal inside my courses tab inside 12th May
tableau batch okay that’s the name of a batch and you can very well go through
these slides okay you have the way you can connect with tableau you have all
the different informations that we had discussed okay
now regarding metadata and data blending working with metadata we had discussed how you can sort how
you can format ok column sorting and formatting all these options come under
metadata management ok and a now today I’ll tell you about what are these
dimensions and measures all about okay so tableau is very intelligent it
differentiates it divides all the different fields available in your data
source into two categories in two dimensions and measures
so basically dimensions are nothing but discrete data okay and measures are
nothing but continuous data so now why why does it say discrete and continuous
how does it differ the fields how does it divide those fields depending on
discrete and continuous nature so now let’s say category or city or country
these values they never change for example you might add a new country to
it but that particular country is discrete in nature
so that particular country name I mean I hope you understand what I mean by
discrete the value of it will always remain constant right but but when it
comes to let’s say a discount or profit quantity or sales your sales might keep
changing every minute your sales might keep changing every year right so it is
not constant at any particular point of time it keeps changing it is continuous
in nature right so this is what it basically uses in order to differentiate
between the fields so dimensions consist of those fields which are discrete in
nature and measures will consist of those fields which are continuous in
nature right so I’ll just show you you know how what major differences are
there between these between the fields you know under these two headings under
dimensions and measures okay so basically when you have a blue color you
it means it is discrete in nature and it means it comes under a dimension and
when you have discount I mean when you have a green color okay it means it is
continuous in nature and it is placed under measure right so let me just show
you how to create a simple view in tableau okay so this is our workspace
this is our sheet one over here okay I’ll just drag any of my fields and
place it into my rows and columns now this space over here is known as the
Rose shelf and this place over here is known as the columns shell
okay so I will place my category in my rows shelf or you can also place it in
your column shelf okay and he’ll have one measure or you know one field under
measure which is continuous in nature I’ll place it in my columns so now as
you can see I have created I I can easily swap these fields in my rows and
columns with the help of this I can over here this is the swap I can ctrl + W is
the shortcut when I just click on this all the fields in my rows will be moved
into columns and all the fields and my columns will be moved into rows so now
as you can see I’ll just click on this icon as you can see my sales has moved
in two rows and category into columns so this is one this is a very simple
visualizations that we have created now okay
so but what will happen we have different marks over here right we have
so many different marks will be discussing about each and every mark
right so now to start with to tell you the difference between dimensions and
measures what I’ll do is I’ll try to let’s say region I’ll just drag and drop
region into the colors mark okay now let’s see what happens I am just
dragging region and dropping into my colors mark so each particular category
category is my dimension okay it is discrete in nature so each particular
category is being divided into four colors now why four colors okay so I
have placed region in my colors mark and region is nothing but a discreet field
okay discreet in a sense I have a countable number of values or it has you
know finite number of members in its column I mean this particular field has
a finite number of members so as you can see I have the color legend over here so
my region field consists of four different values
for different members Central East South and West and each region has been
assigned a unique color right and this indicates the western region southern
region eastern and central right so each particular category tells me the sales
done under each particular region right similarly I will place some other
dimension in color let’s say segment okay you can let’s say segment or ship
mode okay anything let’s place our ship mode inside the color so it is nothing
but am placing or discrete field inside of color mark as you can see it is a
discreet field it has four members of four finite values okay and each value
is being assigned a unique color okay right so when you place on any
particular color your tooltip gives you the entire information required to know
about this particular color or space right so this is what happens when we
try to place a discreet field inside the colors mark okay so now let me remove
this now let me try to choose a field from my measures let me try to place a
continuous field in my colors mark now what happens okay
I’ll take my sales ok sales is already present over here let me take okay let me have my sails as well
or okay let me have my profit any measure for that matter of fact okay so
when you place a measure inside your mark your colors mark now what happens I
do not have a finite number of you know values or members inside my I mean
measure because it is a continuous field okay and as you can see a single color
has been assigned but with a change in shade indicating the lowest and the
highest profit right similarly I can have any measure and this is the way my
view or my visualization will be given a color
okay there’ll be a change in shade and there’ll be a single color which will be
assigned to this field okay with just the change in the shade indicating that
it is a continuous field and as you can see it all my continuous fields will be
aggregated okay and the default aggregation is sum okay so this these
are the basic ways you can try and find out your the difference between this a
discrete and a continuous field okay now I’ll also show you a few other
differences okay let us try and place it in the filter shelf okay this shelf or
space over here is known as the filter shelf
let me have my region which is discrete in nature inside the filter shells right
so now as you can see we have we can filter out the regions okay there are
four different regions and I can easily you know filter out I can include only
these two regions in my view so when I try to have
only central and eastern region and I click apply and okay so now there’s a
change in the chart okay as you can see the the bar level has been changed
because I have included only my two particular regions inside my view I need
the analysis to be done only for these particular two regions okay so I am
filtering out the unwanted data okay or I am filtering only the necessary data
you can have it in any way right so now when I try to place region inside color
I have only two colors because I have chosen only central and eastern regions
I have filtered out the other two regions okay so this is what happens
with a discreet field okay when I try to filter a discreet field now what happens
when I try to filter outer measure or a continuous field okay I’ll have my sales
inside the filter shelf so just drag your measure place it inside the filter
shells now as you can see we had the values with check boxes when we tried to
filter out a discreet field but when it comes to a continuous field we have this
is the way we can filter it out so it initially asks us what is the I mean how
do you want to filter on sales how do you want to aggregate it okay let’s say
as sum that is the default aggregation I’ll go into the next dialog box
okay and now as you can see we have different options over here okay we’ll
be discussing all each and every option in detail when we discuss about filters
topic specifically okay so now I will just tell you the difference I’m just
telling you the difference of a discrete and a continuous field under each
circumstance how these fields behave right
yes so this is how your measure acts okay you can either set a range of
values between which okay I need the values only between these particular I
need only the result only the visualization in between these values in
build inside my view to be used in to my analysis so I am filtering out the other
values similarly I can have this option as well so I can set a minimum value
okay so let it be let’s say this is my minimum value so all the values at least
this or above this are to be displayed in my view I do not want the values
before this range to be displayed okay I can set the minimum value and similarly
I can set the maximum value okay display values only maximum of this number right
and similarly we have one more called special option okay we can display only
the null values or only the non non values and all right so will be will
coming will be coming back to this again during our filters topic okay so I hope
you understood how a discrete field will act in your filters shelf and how your
continuous field will act in your filter shells okay and one more way I’ll just
you know try to create a map now and I’ll show you how your maps are colored
using a discrete and continuous fields okay so in order to clear the sheet up
so I don’t want this best visualization again okay I’ll just use this option
over here okay it’s the clear sheet option okay when I just click on this my
entire sheet will be cleared right so now
I’ll just tell you how to create a map okay again which is one you know
important topic which we will be discussing in detail in our upcoming
sessions but now I’ll just create a map and I’ll tell you how your discrete and
continuous fields act on it right so I’ll just okay I’ll just choose any in
order to create a map I will need a geographical a geographic data type
field right so let me have my state and just double click on my geographic role
field right after which this latitude and longitude which is which are the
auto-generated fields they automatically appear in your rows and columns right
and we have the state information over here so this I’ll just create a symbol
map over here okay right and if I want to name each state all I have to do is
just drag the state and place it inside this label mark okay by which all my
different states are being named now when I would like to color this out okay
let’s see depending on sales okay now when I play sales inside the colors mark
this the same thing happens over here right so the lighter the shade the lower
the sales and the darker the shade the higher the sales so right now I think
California is the darkest so it has the highest number of sales right so yes so
this is these are the basics you know of how your discrete and continuous field
work when you are placing them in the filter shelf or in your marks marks type
whichever type of mark you have okay and we have something called show me over
here right so when you click on the show me you have different shots which are
being visible over here right now they are just grayed out okay so what are
these charts and how can you create these charts right so when you place
your cursor in any particular chart it gives you the information so as you can
see in this space over here so I’m just placing my main cursor in this
particular chart so it’s a highlight table right and what are the basic
requirements in order to create a highlight table so you need one or more
dimension in order to create a highlight table and you need one measure for sure
right so this show me option it clearly tells you so whichever type of chart you
want to create what are the basic necessities I mean the basic
requirements in order to in order for this chart to be created right so let’s
see for a pie chart I need one or more dimension or I need at least one or two
measures right so we have different charts we have bar charts we have
horizontal bar charts we have side-by-side bar charts okay so we’ll
just try out one chart let me have my category
no Kim and I’ll have my subcategory okay and I’ll have my sales right so with
this particular combination I have two dimensions and one measure okay so it
might be in any it might be either in your rows or in your column so that is
not going to affect your the way your you can create charts okay so with these
combination when I have two measures I mean two dimensions and one measure okay
so these are the different shots that I can create okay so by default it is a
bar chart that is being created okay if I want I can have a side by side bar
chart or I can have a box-and-whisker plot or I can also have a packed bubble
okay see as you can see you can have a packed bubble or whichever is precise
okay whichever suits your analysis you can very well go and choose that option
right so as you can see we have a category under which all the different
sub categories are listed out similarly we have the other categories with the
corresponding sub categories okay and this bar corresponds to the sales which
has been done in this particular sub category now I can also swap my view as
I told you okay so each you know box corresponds to a particular category and
all the corresponding sub categories are present inside us now we can sort this
out it is all in a jumbled manner so let me just remove my category okay now I
think it will be better for understanding okay so now I have all the
different sub categories okay and the sum of sales right so when I try you can
easily sort them in the ascending and descending order by the sum of sales
with the help of this shortcut I said I mean sorting options in your
tool bar okay when I say sort okay as you can see depending on the sales okay
depending on my measure let it be profit or any measure in this place it will be
sorted out so I can also try and label my sales okay as you can see I needn’t
go into my tool tip I needn’t place my cursor and then get the information
about sales from the tool tip so my since I placed my sales inside the label
mark over here I’m being able to view all my bar I mean all my bars are
labeled with a corresponding sales of the particular subcategory right so this
is being sorted out in an ascending order from the lowest to the highest
similarly I can also sort it the other way round so by this I can easily find
out which category I can also swap it up so which subcategory has done the
maximum sales okay so by this way I will you know be able to find out the
maximum sales the minimum sales or let me say the maximum profit and the
minimum profit okay just sort it out as you can see we also have negative profit
okay and the label we have sales over here so that’s why there is a mismatch
just remove this up and place profit over here inside your labels so now as
you can see we have the highest profit which belongs to the copiers subcategory
okay and we also have negative profit for a few subcategories and the lowest
off which belongs to the tables so though it might have a higher sales
profit is negative in nature right so you know these are a few basic ways by
which you can keep creating your visualizations just drag and drop your
different dimensions and different measures in your
used okay by which analysis different types of analysis can be performed okay
similarly we have okay I’ll just have my sales back here okay so we have this
tree map over here okay so now this is nothing but a tree map okay so as you
can see over here this symbol indicates the size okay
the size of each box corresponds to the profit okay the color corresponds to the
sales so the darker the color the higher the sales lighter the color the less of
the sales okay and the subcategory I mean is being labeled inside the label
so each box is being labeled with a subcategory okay so you can keep
changing the chart or you can keep changing the measures and dimensions
which are being included in your view right so this is the basic
differences between your dimensions and measures your rock the way it reacts or
the way it performs when placed inside filters and inside your marks and in
your visualizations okay so yes so now I’ll just clear the sheet up okay so now
we have this option over here so this tableau I can over here okay when I
click on that I will be directed to my start page okay this is the start page
of tableau and I when I click on this again I’ll be moved to the sheet from
where I had moved to the start page like for example if I am in my data source
and I would like to go to my start page and again I’ll be moved to the data
source sheet right so then we have undo so in tableau we have n number of undos
you can keep on undoing your data n number of times okay there is no limit
for undoing your data in tableau right so this is the tool I mean the tool bar
and the undo option over here okay and this is the save option okay in case you
want to save any particular view you can use this options or you want to save all
your visualizations okay you can use this options okay and this is about the
data connections okay you have to add any new data source you can do that okay
and this is you can pause auto-updates in case you have assigned a scheduled
refresh right in your tableau server while working in your
Desktop a blow desktop over here in case you did not want any updates to
interrupt your analysis right you can very well pause the updates okay and
then we have this new sheet option over here so we can create n number of sheets
okay in tableau and this is one shortcut by which you can create a new sheet so
when I just click on this my second sheet is created I had only one sheet
and this is my second sheet okay or you can also go into worksheet and create a
new sheet right and similarly when you click on this drop-down arrow you have
new worksheet new dashboard and new story okay
these are the ways by which you can create a new sheet or dashboard or story
right and we have something called duplicate over here okay for example if
I have a based some visualization that I have created
in this particular sheet okay so if I want this visualization to remain as it
is okay as well as I want to perform further analysis in this visualization
itself right so I can have the sheet as it is I can create a duplicate so I
needn’t go to my other sheet and start building this view from the scratch this
is this might be a very basic view right so it can be done in seconds but when we
have a very complex visualization with many dimensions and many you know
measures of fields in my marks okay and with filters and so on so when I want to
create a duplicate of this particular visualization and I do not want to
perform all these actions again right from the scratch I can create a
duplicate okay by which sheet one of two is created so I’ll have my sheet one as
it is and I’ll you know make changes to my sheet one and so on okay so this is
the use of this duplicate icon and this clearing the sheet I’ve already told you
everything in your sheet gets cleared up and when you click on this drop-down
arrow you have you can clear your sheet okay you can clear the only the
formatting of this particular worksheet and all these options okay you can clear
the filters alone access your sizing and so on okay this is the option of
clearing we have the swap option okay we just now discussed about it okay it just
swaps from the the rows and columns the fields in your rows and columns the
sorting in ascending and descending order okay we have this highlight option
we have different types of highlight okay we have around five four to five
different types of highlighting options which will be disgusting in when that
particular topic comes okay and this option is just to enable or disable your
workbook highlighting workbook is nothing but
a collection of worksheets dashboards and stories the entire set is known as a
workbook right so you can enable or disable your highlighting okay – your
entire workbook or you can enable or disable the sheet highlighting if you
had one okay and highlighting can be done by any one of these fields so
okay so these are the options which comes under highlighting okay this is
actually a very shortcut menu for highlighting okay and this is nothing
but you can hide the mark labels okay and you have this fix access this you
know is used when we have our maps in our sheets okay
it’s used a fixed axis okay this is about the size of of you right now it is
the standard size okay if you want to fit with the entire width will be
utilized okay fits height is similar to the
standard view okay because the entire sheet is being I mean the height is
being used okay an entire view is just nothing but your fit with okay so when
you have complex visualizations this will work accordingly but basically this
is what happens when you change the type of view the size in which your view is
to be done okay and this is nothing but the show and hide cards okay so these
are known as cards or shelves so this is my page page card or page shelf this is
my filters card or filter shelf okay this is my marks card or shelf and so on
so if I want to hide them or if I want to unhide them I can vary values these
options so right now we have the marks card filter shelf page shelf row shelf
column shelf okay my title which is nothing but this sheet one over here it
is being visible okay and I we have something called caption so if I try to
make caption visible as you can see this is just summarization of what is being
visualized in this particular sheet okay so this sheet gives the information
about sum of sales for each category right Karla shows details about region
right color shows details about region and the marks are labeled by the sum of
sales so by default a caption is created with the fields that are used inside the
visualization if you want you can manually type in any caption okay some
extra information that you need to provide inside I mean about this
particular sheet okay and we have somebody okay somebody is nothing but
similarly the sales for this particular measure okay we have the sum the average
all the different aggregations right and we have legends as well so what are the
legends right now we have only the color legend okay we have shape legend and
size legend so we have the size mark over here okay and we have shape as well
so when we have okay let me just remove this region from
colors okay my color legend is no more visible let me have my region inside
sighs okay as you can see there’s a change in size for each particular
region so as we had colors differentiating between there are four
regions now it is being differentiated with the help of this size mark so this
is the size legend so these legends they just give information as in for which
particular size belongs to which particular region right so it’s just
like a key to whichever mark let’s say size or shape or color so this is all
about legends okay and filters we can filter this particular visualization
using category region and some of sales because these are the three fields which
are being used in our visualizations let’s say I want to filter it by
category okay as you can see an interactive
filter is visible over here and automatically my category field has been
moved into the filter shelf okay so now I can choose any one any any
categories for which I want the view I mean which get whichever category I want
to be visible in the view if I want only furniture category only that is being
visible if I want only acknowledge II only that is being visible right so this
is all about filters okay and highlighters so I can also highlight
using this category and region okay I cannot highlight using my measure and
that is why I have only my dimensions over here okay
so let’s say I wanted to highlight by a region
okay and this highlight is automatically created okay and when I click on it all
the four different regions are available and I when I keep moving on each
particular region that particular region gets highlighted okay this is a very
basic feature of highlight right we have different types of highlight okay we’ll
be discussing all these things in detail right so this is default highlighting option right I can
also highlight it by category okay we’ll just try that I’ll have all my I’ll just
remove category from filters okay and I’ll try to highlight using category so
I have highlighting of region and category now I want only furniture to be
highlighted and inside furniture I want only central region eastern region okay
since we do not have filters I’ll if I would have filtered the furniture option
okay only the region of furniture will have ever have been highlighted but
since highlighting is just highly we have all the fields I mean categories in
the view okay they are not removed from the view like filters when we had
filters we had the other categories completely removed from the view okay
but that’s the basic difference between highlighting and our filters okay and so
I can highlight using these options okay this is just to make your visualization
more interactive and interesting okay then we have this presentation view okay
which can be used when you go in for presentations right and we also have the
share workbook with others okay we will be discussing about that when we move
into about publishing and sharing after creating a complete workbook okay and so
we have two sheets now okay let me just tell you a little about how a dashboard
looks like with what we have created today okay let me delete the second
sheet so now I have sheet 1 and a duplicate of sheet 1 in which I have
made it a few changes okay so you can also you can create a new worksheet okay
or a dashboard or a story by either going into worksheet new worksheet
dashboard new dashboard of story new story or you can use this tool I can
from the toolbar or you can use these options over here so new worksheet new
dashboard and new story okay so this is how a dashboard looks like all the
different sheets will be visible right here okay all I have to do is just drag
and drop into my view right so all the filters legends everything will be
visible in our dashboard as well okay so this is how we create a basic sheet and
with the help of the sheets we create a dashboard and story is nothing but you
have your sheets your dashboards everything in a single view and that is
your storyline okay so we’ll be starting with this note on
file types okay so as I told you dot w TW B which is nothing but the tableau
workbook this is your default file type in tableau okay it holds all the content
on your worksheet your dashboard the it just stores the entire workbook which is
created okay it stores all the information regarding a particular
workbook so as the extension as the name tells you it’s tableau workbook it holds
all your worksheets dashboards stories everything which comes under a workbook
write it all it carries all the information regarding your data source
connection and also the metadata created for that particular connection okay it
has information such as like what fields are being used in each view or in each
sheet okay how your measures are being aggregated what are the different
formatting that you’ve applied the the different styles are formatting anything
that is made to the dashboard or worksheet or story everything will be
saved everything will be will I mean this
extension this file type will contain all these sorts of information okay it
but one main point about this file extension is that
it relies completely on your live data source okay as it does not it contains
only your workbook it does not contain any data okay within the workbook file
so because of this it is completely reliable or not live data source
connection okay so what is the use of this file type this file type you know
dot twb your tableau workbook can be shared only to those people who have
access to the data source because as it does not contain any data as it relies
completely on a live data source the people whom you share this workbook with
should have an access to the data source so only then they will be able to open
the workbook and you know see what particular analysis is being made inside
your workbook right else there is no point in sharing this workbook without
the data with which for which this workbook has been created right so this
is the default file type which will be provided while saving a particular
workbook in tablet okay next we have the tableau packaged workbook we have it
over here so it’s dot t WB X okay so it bundles the data with workbook with your
corresponding workbook right so we had only your workbook information in dot
twb but where as in contrast this packaged workbook it contains both your
workbooks and the extracted data right it also can
includes any picture actions any geocoding that you’ve been added to your
workbooks okay it’s just like you can compare it with a zip file right if you
rename this tableau work packaged workbook as a zip file
you can open it in Windows and you can see all your workbooks and corresponding
data files okay it has the extractor data so we have a file an extension for
the extracted data as well will be discussing after this actually it’s
known as the taut dot TDE file as you can see over here okay it’s the data
extract file so your packaged workbook dot twx will contain your extracted data
as a dot PDF file okay and these files can be shared to clients who do not have
access to the data source but who need to view the workbook right so your dot
twb your tableau workbook will contain only the workbook information whereas
your packaged workbook will contain your extract file along with your I mean
along with the corresponding workbook okay and when you want to chair to save
your file as a packaged workbook when you want to save your workbook with this
particular extension dot twb X you will have to go in to an extract connection
and then save it as a packaged workbook you cannot save your workbook as a
packaged workbook when you are in a live connection okay because it includes a
data extract file you have to change your connection as extract by which an
extract will be saved in your tableau repository and after which you will be
creating a I mean you will be saving your workbook as a packaged workbook
which will contain the extract data file along with your workbook right and we
have the dot TDE the data extract file okay and as we had discussed yesterday
during the live and extract connection when we were working with an extract
connection before moving into the sheet tableau had asked me to save the extract
in the tableau repository right so that is the dot TDE file so as we know
extract files are nothing but they are just a snapshot for a okay or a local
copy of the entire data okay it doesn’t store any connection string okay it
shares only the underlying data and it cannot be refreshed
right it improves performance as we discussed with our extract connection
yesterday so when you have this extract file in your system your processing
speed will be increased when compared to a live connection okay so this is about
the extract file and the dot d de is a file extension which was available in
tableau initially but as newer versions were launched we have something called
dot hyper in which our data extract is being saved nowadays ok it’s a new in
memory data engine right and this with this hyper with this new data engine the
extracts and hyper they take advantage of the improved data engine ok it
supports like faster analytical faster query performance is being made right as
when you compare with the data engine which was before ok and you can also
save larger extract with a faster analytic analytic and processing speed
when it comes to your dot hyper file extension ok you have many other
benefits like you can create and refresh you know faster when compared to your
dot TDE file and there’s one limitation when it comes to your dot hyper file
you cannot downgrade okay you cannot downgrade because it’s been launched
only in the latest versions of tableau but because when you try to downgrade
you will not be able to downgrade it since this particular file extension is
not available in the lower versions ok so this is about the dot TDE or data
extract file then we have the data source tableau data source dot TDS file
extension right so when you connect with your data source for the first time ok
you will have some modeling works or you know formatting works to do ok and this
particular dot CD is file it contains the information required like to connect
to your data source as well as other custom and calculated
fields such as changing aggregations creating groups and sets okay all these
changes which are being made inside your data source here in tableau will be
saved in this dot tedious file okay so when you’re trying to change the
metadata changing the metadata in the sense you will perform some formatting
options you will try to split your site to try to sort it out in some particular
order that you wish to see all these kinds of information are stored in this
dot TDS file okay and by saving these changes as a TDS file you can make use
of the metadata changes next time when you use the file okay so that’s the use
of this TDS file it just saves the path and the necessary metadata changes all
these kind of information but it does not contain the actual data it is not
like your data extract file which will have the actual data your data source
dot TDS file will only have the information regarding the data source
but not literally the actual data right so and similarly just like our workbook
and packaged workbook we have the data source and packaged data source file
extensions over here okay so as we went through the packaged workbook so this is
also something like this packaged data source file will contain the Tod dot DDS
file over here which will contain all the information the the path the way I
mean all the metadata changes all those necessary information about the data
source so your package data source will have your tedious file as well as your
data extract right so with this package to data source you have your extract and
the necessary changes regarding the information regarding the necessary
changes made to the data source right when someone has access to your data
source and would like to view the data with all the metadata changes
right you can share the package the datasource
to them okay as it contains extract data and also the metadata changes that you
have made as per your desire okay so no worksheets or dashboards are you know
contained within this package to data source it has only extracted data and
the changes made to the and the metadata changes okay and it can refresh the
extract data as the data sources within the TDS X file right when you have an
internet connection you can very well refresh your extract just like we
normally do with the extract file that we have okay and it can also be used
offline since it contains an extract okay so this is all about the packaged
data source file and we also have a few more that are not listed on the stable
over here okay very some two or three more simple ones right we have the dot
TBM file TBM stands for tableau bookmark now when do we use this tableau bookmark
file extension right so it saves the worksheets when working as a team to
create create a workbook for example you are in an organization you are planning
to create a workbook with say some 10 to 15 sheets and you have divided this work
to your team which contains 10 to 15 members so each member will be assigned
to create a sheet and they will save that particular sheet as a tableau
bookmark ok after which you will be combining all the bookmarks which means
you’ll be combining all the sheets and you’ll be creating a a complete workbook
ok with the help of all these sheets so each user or each team member has
created a sheet and saved it as a tableau bookmark dot t BM file and after
which you will be combining all the worksheets to create a workbook so when
you work as a team when you to share the work among you know n
number of people you can use this particular file extension okay and you
cannot create a bookmark from a dashboard page because your bookmark
will contain only worksheets right that is one important point
so only worksheets can be saved with a with this particular file extension dot
TBM once you move into a dashboard you will not be able to save a dashboard
itself because dashboard is a collection of worksheets so the lowest granular
level which is the worksheets can be saved as your bookmark file ok and then
we have something called tableau Preferences dot TPS file ok
so like why do we I mean what type of information that this file extension
consists of when you wish to create a custom color palette as in for your
organization you will have some particular color or some particular
pattern to be present in all your worksheets some particular theme for
your workbook like company brand colors or logos or any such kind of information
which is unique only for your organization when you need this type of
custom changes you know to be present in all your worksheets ok you can save
these in Azure dot TPS which is nothing but the tableau preferences file and
what is the advantage of saving these as a file ok you can use this file across
all your workbook because these changes will be applied to your entire workbook
very easily you needn’t go manually and keep applying this custom changes these
color palettes this theme for each particular worksheet or dashboard so
when you try and save a file with this extension your entire workbook will have
the same you know color palette or theme which you have been used or saved in
this particular extension a file extension ok
and we have one more which is the tableau mapsource dot TMS okay so when
we need to create a map with tableau okay we can also create custom maps
either you can you know download it from a mac box you can get it from a map box
okay or might be you can get a custom map from the web mapping service WMS
server okay you can use all these custom maps right here in tableau okay we’ll be
discussing about this in detail and practically with examples when we disk
we move into our mapping module okay so and generally this custom maps I used to
save with this file extension tableau Maps owes dot team a TMS file okay and
when you want to save the custom maps with your colleagues okay who are
working on the same workbook or with the same process of analyzing your but this
particular data source you can share this file extension with your colleagues
so that your custom map will be shared to the people whom you would like to
share it okay and next we have the lesser spotted file extensions you know
this is just for information in case you come across any of these file extension
you should be you should know what it means so they are very less spotted
because they are the file extensions regarding the license activation okay we
have something called dot TLD it’s the tableau license disconnected file
extension it contains you know information regarding the license of
tableau and we have something called dot tlf which stands for tableau license
file ok it contains the license file of tableau and B you also have dot TLR file
which is nothing but the tableau license request return or response so
all these files are lesser spotted and it is something which is related to the
license activation so we wouldn’t be using that much when we work with
tableau so apart from these so the eight file extensions that we’ve discussed
today are will be used while working you might come across all these things and
you might make use of all these file extensions right so we started with dot
twb the workbook tableau workbook which contains only the information regarding
worksheets dashboards or collectively your particular workbook ok the tableau
packaged workbook which is the dot twb X file which will contain a data extract
file along with your tableau workbooks so that whoever is not able to access
the data source directly they can be shared this packaged workbook which will
contain the extracted data and the workbook which has been made for the
extracted data ok and we have the dot TDE the data extract file in which our
extract is saved we have the data source dot TDS which contains all the metadata
changes which have been made when you first enter in when we when you first
open your data source and it also contains the path ok and but does not
contain the actual data and just like the packaged workbook we also have the
package data source which contains the extracted data file with the dot GDS
data data source file which contains all the metadata changes done to the
extracted data ok and apart from these we have the ok bookmark is also
mentioned here okay so bookmarks it contains a single sheet so apart from as
we were talking about the tableau bookmark you can save only a particular
sheet as a bookmark you cannot save your dashboard as a bookmark so I’ve been
working as a team this bookmark extension will be very useful and apart
from the file types which I mentioned over here we have two more which is the
dot TPS tab no preferences and tableau mapsource
okay and I blow preferences as I told you it has the particular theme of color
palette for your organization it contains that information and your
custom maps are stored in the dot DMS file ok the table map source file
yes so this is all about the different file types that we have in tableau and
while saving your tableau workbook you can just toggle between these different
file types and save them ok and as per your requirement right so this is all
about the different file types so after which we’ll be moving into our
new topic today which is about data join and data blending okay so for that we’ll
go into a tableau and we’ll try to connect it with our sample superstore okay yes so we have connected a sample
superstore data source with tableau now right so we have three sheets now we
will first discuss about data joining what is data joining in tableau okay so
data joining is nothing but you can join any two tables or two sheets from the
same data source file okay you can join any two tables in your tableau and
perform your analysis so when you want to join any two or three or you can join
a maximum of 32 tables in your canvas over here at one point of time okay so
when you try to join you should have a common field or a key or a foreign key
the common field between those two tables by which the join will be
performed right so and data joining as I already told you can be done only
between tables from the same file okay you though you have similar information
in another excel file and when you try to have two data sources
you you should go to a data blending option which is much better in that case
okay in our earlier versions we did not have an option to join when we had I
mean to join tables from two or more data sources but in our in the latest
versions we have the joining process also but the way it works
definitely differs okay the how data join and data blend works the first
we’ll see that we will see the difference is one by one today okay to
start with we will stick on to data joins first we’ll finish off data joins
and then we’ll move on to what is about all about data blending okay so data
join basically can be done between tables or sheets which which are which
belongs to one particular data source okay so here we have three different
sheets we have orders people and returns and I’ll have my order sheet and now
I’ll try to join my second sheet so yesterday we had only one sheet in a
canvas and we were working with this particular sheet we went into a sheet we
tried to create visualizations okay so now we’ll be trying to join another
table with the existing table and let’s see what are the different types of
joints and the requirements for a joint to be performed okay so now as you can
see the inner join is the default join when you you know bring in two tables
inside your canvas so this is the default default type of join which takes
place and only because you have a common field a joint is being possible over
here so when two tables do not have a common field or a key to join you will
not be able to join them in either of the type like we have four different
types there is no common headers between those
two she then old a you that join icon or it would not like do we have to hold
I’ll just show you that now we try to join orders and people right so now
let’s try to join people and returns so people has person and region and when we
try to join it with returns so this is what it tells it gives a red exclamation
mark telling that there’s no common key between both so as you can see we have
person regent returned an order ID in the returns table so there’s no join
which is being possible so this is what it shows when a join is not possible
okay good thank and in such cases if we have we might
sometimes have you know a similar column in our other table in a second table as
well with a different name as I just told you we have region over here okay
and in case we had so region will consist of information like whether it’s
the north south east or west so if we have the similar content in our other
table but with a different column header let’s say market okay at that point of
time also tableau will not identify the key because the header names are
different the column header is different so at that point of time we can tell
tableau that this particular column in this table is equal to this particular
column in this table and please you know allow a joint to be made between these
two tables so that is possible so if we have such scenarios we can definitely do
that okay and in our data blending example that I’m going to show you today
we have such a scenario so we’ll just go through that when we are discussing with
that particular example ok so right now we will discuss about the joins
yes so as you can see initially we have and just type some random number and it
tells me the exact number okay it has all you can just go into this icon over
here and find out the total number of rows which is available in this
particular table okay so we have these many number of rows in my orders table
so when I try to create a join okay we have the same number of rows because
the key the common key is nothing but the region so all my all the data which
is present all the rows which is present in orders is being matched with all the
rows which is present in the people’s table so there is a complete match as we
have an inner join so that is why we have the same number of rows rows ok and
inner join is nothing but all the information all the rows which are
common which match in both the tables will be displayed the the explanation
for all these joints is just like as we have in SQL inner join left right and so
on right and left join as you can information from my left side table will
be included and all the information which match both will also be included
right so this diagram tells you and when you place your cursor you have the
necessary information it includes all values in the left table and all matches
from the right table right and members without matches will show up as nulls on
the right ok so right now we do not have any null values because every row in
orders has a match in your peoples they are people table right and when we try
to move into a right join since we have a complete match between these two
tables now we are getting the same number of rows over here and right join
as your explanation tells you it includes all the no rows from your right
side table including the matches from your and a full outer join will again
have all the rules from all your tables okay so these are
the of joints that we have in tableau okay inner coin is the default join okay
and we’ll just try to join two other tables now okay let me have orders with
returns so now with orders and returns if you
want to find out which is the key okay this will be displayed right over here
your order ID of orders table is being matched with order ID of your returns
table and by default itself in our joint okay and as you can see there is a
change in the total number of rows because only these many number of rows
are being matched with these two tables okay and when we try to change the type
of join okay you will have more number of rows
as you are including all the rows which belong to your order stable which will
have all the nine thousand nine hundred and ninety four rows and those that
match with returns will also be included okay so that is why there’s a change in
the number of rows and again when you move on to your right join you’ll have
the rows from your returns table all the rows from your returns table okay will
be matched I mean and all those matchings with the left side table will
be included and again your full outer will have the entire rows when you join
both of tables okay so these are the different types of joins right and when
we do not have a key to join you can very well tell tableau in case you have
the same content with a different color column header you can tell tableau to
create a join okay and before we move into blending into data blending
examples okay we’ll just have a look at something called Union which is
mentioned over here right so we have something called new Union okay
Union you might ask me what is the difference between new Union and outer
join full outer join right it is similar to Union so you might ask me what is the
difference between full outer join and Union so Union if your data supports
Union only then this option will be displayed over here right so only if
your data supports Union this option will be displayed over here only if
there’s a possibility to combine all the different tables or you know or any two
tables as a union this option will be displayed here else it will not be
displayed over here okay and when it comes to joins it appends the result
sets horizontally right that is one point when it comes to joints but when
you consider Union the it your Union appends the result set vertically okay
so that is one difference between your join and you knee
okay your Union will just combine two or more tables okay by appending values
from one table to another but in a vertical manner right so if you want to
create a union you have to just double click on this you will have the
different ways by which you can perform the Union you can just drag and drop
your fields inside the space over here to the tables that you would like to
perform a union on or you have this wildcard tab over here okay and you can
include for example if your you have n number of tables and you want all the
tables with a particular you know suffix or prefix let’s say you can use this
Asterix sign okay and mention for example if you have
the month information though for example at say 2019 you have Jan 2019 Feb 2009
teen you have 12 different tables or you have n number of tables for all the
years with the months as Jan 2018 Jan Feb 2008 een and so on till 2019 and if
you want to come make perform a union of only one particular year let’s say I’ll
say a strict 2019 or a strict 2017 all the tables which consist of this
particular suffix 2017 will be included in the Union okay you can also try and
exclude that okay it’s all up as per your requirement okay and and if you
want your expand to be you know search all your sub folders and all the
different folders which is available in your desktop itself you can do that okay
so this is all about the Union so I think we will move into our data
blending now okay and and when you create a join okay I have my orders and
my people can you take this present example and explain you in Ian the
example present okay I’ll get the order seconds okay yeah we right now we don’t
have the tables with you know we okay I’ll just try to make a union of these
tables over here and explain but with regarding those suffix and prefix which
we try to include we need to have tables with similar suffix or prefix okay but
now I’ll try to make a union of these tables and I’ll just show you okay so I’ll just double-click on this
Union okay I’ll bring in my orders just drag and drop it inside the space over
here okay so now I’m including my orders table inside the Union right and
similarly and am bringing my peoples as well okay and if you want you can have
your returns as as well or you can stop with this it’s all up to you okay so
this is how you basically create a Union just click on apply and okay okay so as
you can see there’s a union being made this is the symbol over here okay and
you hand the the the table name is completely changed right you do not have
something called orders or people okay the Union Union is something that is
being visible over here okay so this is how you create a Union and you’ll
definitely have null values when you try to combine yes as you can see you have null values
when there’s a you know mismatch when you do not have sufficient values it
will have null values and this is what Union is all about this is very similar
to the full outer join okay but one difference is that the way it is being
computed so Union is computed you know it appends the result sets vertically
and your join will append the results it’s horizontally when you have you know
more number of tables or more appropriate tables when you combine such
for example if I have the month tables as I told you so my Jan will have 30
days and similarly all my months will have similar type of information so when
I try to combine them you’ll get a better view you know when you combine
that type of tables so at those cases Union will work you know very effective
Union will be very effective in such type of use cases right so basically
this is how you create a Union okay and field names are in the first row and you
can edit the Union again if you want you can you know move in your tables or move
out you can include all these information you can try and edit them or
if you want to remove the Union and sometimes this this you have this option
called generate field names automatically okay sometimes you might
not have field names for a few columns okay at that point of time you can
manually create a field name you know in those cases when you uni when you try to
make a Union you might have a few tables which might not have column names or
which might not have column names which are similar at that point of time you
can you know manually do that or ask tableau to generate those field names
automatically with the help of the content which is present inside the
columns okay and you can just remove the Union with the help of this option so
this is what you create this is how you create a Union basically when we have
appropriate tables you know it will be more effective
it depends totally on your requirement when and where you want to create a
joint or a union between your tables it all depends on your analysis process
okay and now and just show you when we have a join which is being made over
here when you go to your sheet okay you have your dimensions and measures column
okay right now we do not have any measures which belong to this people
table we have only two columns or two fields in people which are discrete in
nature right so this is because whenever you create a join when you go into your
sheet you’ll have your dimensions divided into you know those many number
of tables which belong to your join so these dimensions belong to my orders
table and these dimensions belong to my people table and these are the measures
which belong to the orders table since people do not have any measures as such
right so this is how your sheet looks like when you have created a joint over
here okay so to explain about data blends I have
two Excel files with which we will be you know performing a blending action right so
for that I’ll just close this up I’ll just open my tableau again and I’m going to
add two data sources to perform our data blending action right so first I’ll have
my data blending sample 1 which is nothing but the office sales ok and
before that let me just show these two different files over here ok we have
something called office sales and coffee sales over here
ok so this is my office sales so I have four different columns over here the
state code the state name the market and office sales ok and we have coffee sales
over here which consists the information regarding this particular data so select
product type your product name state region and coffee sales so as we are
trying to create a data blend ok why we are creating a data blend because these
are two different Excel files these are two different data sources so when you
try to combine tables from multiple data sources data blending is the option that
you should go for ok and as you can see we have one common field which is
nothing but the state in both my Excel files right and we have something
called region and market over here as I just now told you we’re explaining about
data join the content is just the same we have all the four different
directions which are mentioned over here right but the column header is different
so tableau will not recognize this as a key it will recognize only state as a
key so right now we have state as a common field which will be recognized by
tableau but in case we do not have the state column over here tableau will not
recognize region and market as a key so at that point of time we have to edit
the relationship between these two excel files okay and we have to tell tableau
that please you know create a blend with region and market as the key right both
these fields are common in nature so please create a blend so we will have to
edit the relationship manually right so we will see first with the common field
which is already available how blending can be done right and then we will see
how to edit the relationship in case when we do not have a common field
between the multiple data sources okay so this is all about our data source the
excel files that we are going to work with right okay so now I have and
there’s one more point over here when you have your office sales connected to
the tableau and then when you add when you try to add another data source with
this option okay it means you are assigning of the sales as the permanent
primary data source and your coffee sales as the permanent secondary data
source and just tell you that we will go into the sheet first okay I have my
office sales I have only one data now one data source
excel file connected to tableau right now okay and now with the help of this
option over here add data source okay I’m just gonna
click on this I’m going to add another excel file and that is going to be my
coffee shop sales okay and as you can see when I go into my sheet I have two
different data sources over here so when I click on office sales the necessary
information regarding office sales is displayed the dimensions and measures
which belong to only to office sales is displayed and when I go into my coffee
shop sales data source the dimensions and measures which belong to this
particular data sources display right over here okay but when you try to you
know add your data source right from your data source sheet over here with
this option okay what happens is we’ll just see that okay
so this is when I added a data source after moving into my sheet okay so now
if I can assign I can change the primary and secondary data source as my desire
now how do I do that how do I assign the primary and secondary data source okay
so when I have so state is the common field between these two I’ll just have
my state okay and I would like to compare the sales of the coffee shop and
the office sales in one single view right so as you can see I dragged the
state from the coffee shop sales into my columns and now there’s a bluetick which
is being visible right next to the cylinder over here and as I told you
yesterday we have one cylinder because we are connected in a live manner and if
we have two cylinders we would have been connected in our extract manner right so
since we have only one cylinder over here and it has a blue tick this means
that your coughs you have chosen coffee shop sales as your primary data source
right now I’ll have my coffee sales in the view in my rows and I’ll go into my
coffee sales just click on the other data source and you have this link icon
over here which tells that which tells you that stay
it is the key with which both your data sources has been linked okay and I’ll
drag my office sales in my rows as well okay so now as you can see there’s an
orange stick over here indicating that your office sales is the secondary data
source now what in what way does this affect you know your analysis your your
performance what in what way does primary and secondary do datasource
affect your review okay so now data blending is nothing but it’s a left left
outer join so when you blend tables from two different data sources the join
which is being made is the left outer join okay that is the only type which
can be made when it comes to data blending so when you say left outer join
you need a table on the left side and you need a table on the right side right
and I hope you can visualize what I’m trying to say left outer join okay I’ll
just show the symbol for left outer join right now we have only one okay I’ll
just tell you that after finishing of this okay and for when you try to blend
tables from two different data sources the join which is being made is nothing
but the left outer join so your primary data source will be the table on the
left side and your secondary data source will be the table on the right side so
all the information from your left side table which is your primary data source
will be visible including the matches from both the tables right and that is
one way which by which you know your primary and date a secondary data source
will affect your view right so right now we have coffee shop sales as our primary
data source and office sales as the secondary data source and as you can see
we have two null values over here because we do not have these two states
in our office sales it is being you know displayed as null values okay but in the
case of an inner join this will never happen
only the matching values will be displayed but since it is a left outer
join okay all the information in my coffee sales are displayed but only the
matching ones in my secondary data source are being displayed with null
values right I it is showing greater than two nulls
right what is the meaning you have to love it no it is not greater than two
nulls it just it is just telling that it at least has two nulls it’s just a
symbol to indicate that it has two nulls so greater then is has nothing to do
with this symbol over here okay it’s just something like which tells me that
it has two nulls so there’s nothing greater than which is related over here
okay please do not confuse this sign with a greater than sign it just tells
me that there are two nulls that’s it it has at least two nulls in the sense and
I’ll tell you we will just go into our you know sheets again and we’ll have a
look okay as you can see we have so we have coffee shop sales okay as our
primary data source okay we have so many different know states over here okay yes
I hope you are able to see it now okay and we have
we have one of the different states we have care law we have deli we have MP
and punch-up right so we have these four different states in our primary data
source okay and we have only these two states which are common to our primary
data source we have only Delhi and Kerala which is common to my primary
data source so Orissa is not being you know Orissa is not at all included in my
blend because it is a left outer join so I have all the different states in my
primary data source which is being visible over here and only the matching
values are being displayed in my office sales you see as you can see this is my
coffee sales which is the primary data source it has all four different states
the values for all the four different states but when it comes to office sales
I have only the matching values displayed over here and I have two nulls
because two values from the primary data source do not match with my office sales
and that is why it tells me I have two nulls over sure right when we try to
work it out the other way round right we will try to have office sales as our
primary data source now and we’ll try to have a coffee shop sales as the
secondary data source now now let’s see what happens okay
so I’ll go into my second sheet now as you can see every sheet the primary and
data source that we choose in every sheet is you know independent of the
next sheet like every single sheet is independent of each other so if I choose
coffee shop as primary and office a secondary this will not be reflected in
my second sheet my second sheet will be we’ll start from the scratch so right
right in this sheet I can decide the other data source as my primary and
secondary and vice versa right so we had a coffee shop as primary and office a
secondary will move into a second sheet will have office sales as primary as X
State from my office sales okay and we had only three states in our office
sales right see we had we have only Delhi Kerala and Orissa and all the
states are being visible over here but when you try and I have my office sales
as well right so I am going into my coffee shop muscle my office now my
office sales has been made the primary data source I’ll go into my coffee shop
and I’ll take my coffee sales and place it right over here
now as you can see we have one null over sure though we had around four different
states in our coffee you know sales table only three are being visible
because these three belong to my primary data source and or only the matching
values are being displayed over here with a null value in my coffee sales so
I hope you understood you know the the change that is being made because the
changes in the primary and secondary data sources okay so the basic join
which is by which this these two you know tables are being combined is by the
left outer join so whichever is my primary data source this that particular
data source all the information regarding in that table will be
displayed and only the matching ones from the secondary data source will be
displayed I hope this point was
clear so far okay the difference between and you can also see the symbol over
here my office sales has an orange stick which tells me that office sales is a
field or a measure which belongs to my secondary data source and similarly over
here you have I mean when you go onto your second sheet you have coffee sales
which is you know given with our orange tick indicating that it is your field or
measure from the secondary data so in this particular sheet right so this is
the basic you know way of how you blend your data okay we can also create
calculated fields we can also you know apply some blending calculations if we
require right so in my in our example right now we have office sales and
coffee sales now I would like to see the sum or the total sales you know the sum
of coffee sales and the sum of offices I want another bar graph which tells me
the total sales okay we can perform this you know this type of calculation this
is known as a blending calculation we are trying to blend fields I mean
measures from two different data sources we are combining in it into one
calculation and we are trying to you know display that information as well in
our view right so this is known as the blending calculation so tableau allows
us to perform such calculations right okay but before that let me just tell
you one more point so I tried to you know add a data source after moving into
my sheet now what happens or why I did not try to add a data source from this
option mentioned over here okay there is a small change by doing by adding your
secondary second data source using this Add button and by using this add data
source button after moving into your sheet of
let’s see what happens what is the change that is being made okay and just
delete the sheet okay and I’ll just clear the sheet and once you clear the
sheet the blue and orange tick marks are disappeared because right now you can
choose your primary and secondary data source as per your desire right so I’ll
just try to you know close my coffee shop sales and I’ll go into my data
source so right now I have only my office sales and in my sheet as well I
have only one data source to which my tableau is connected right so now when I
try to add a data source with this option over here okay
I’ll add my coffee sales right we have office sales I am adding another data
source which is my coffee shop sales so now as you can see I had office sales
initially which is blue in color over here okay there’s a vertical line right
next to it indicating that it is your primary data source okay and we have the
coffee shop data source over here in which is orange in color indicating that
it is your secondary data source and you know by default there’s an inner join
which is being created okay and similarly you have this blue and orange
line over here indicating that this will permanently be your primary data source
and this will permanently be your secondary data source okay and this is
one difference by adding your data source using this option and after going
into your sheet so once you add the data source after going into the sheet you
can manually change the primary and secondary data sources you know as per
your requirement per sheet but when you try to add another data source in your
data source you know page itself this is the point which happens this is the
thing which happens you know your first data source will be made the primary and
your second will be made though secondary data source and there’s an
inner join which is being created okay and this is not you can ask me how do
you how they how is there a joint being created when we have tables from two
different data sources okay so this is a feature that tableau has introduced in I
think after tableau and it from tableau 10 that’s the version from which this
feature was introduced but before that when you wanted to you know combine
tables from multiple data sources blending was the only option okay you
can try you know joining your tables as well but one disadvantage is that your
primary and data a secondary data sources will be fixed over here but in
our case when we try to blend the data okay
we had the option to you know change to move between the primary to change the
primary and secondary data sources as per our desire so again I’m going into
my office sales I have only one data source and I’m
going to add another data source with the help of this icon over here
so again we have will go into a sheet again we have two different Excel files
over here two different data sources okay
and we just now tried to you know bring in our state and the sales information
from both these data sources now in case if we do not have a column which was
common in between these two data sources so now what can be done in such a
scenario right I told you we can edit the relationship between these two so
though we have state in our examples as a common okay as we have state as a common field
in case if we do not have state this thing was starting nothing but will be
like an left outer join kind of exactly but when you do with the data source
section inner join yeah that is you are creating
a join over there that’s what I’m telling you initially we do not have
this option till tableau ten version so we cannot join tables from two different
data sources but now we have that option as well we have this you can change the
type of join we had inner join when we try to you know have to multiple when we
had two data sources right in a data source page so in that case you are
performing a join but in our example right over here that I’m showing you
this is where we are trying to blend data so there is a difference between
data joining and blending so I hope you understood now data blending is nothing
but left outer join but when you have a join symbol over here you can very well
keep changing the join because we have you know added the mult
other data source right in our data source sheet so there’s just two ways
okay and by this way can be done between two different data sources yeah it can
be done that’s what I’m telling you till tableau before tableau ten version that
was not possible but right now we have these options as well but the way it
looks the the way it your you know your workspace your dimensions and measures
look will be different when compared to that of data blending as I showed you we
had time so right now if we are creating a join will have dimensions will have
the dimensions under you know each table mentioned separately right
just show that once more okay I’ll remove this I have only office sales now right
so now I am adding another data source from this ad option over here okay and as you can see by default it’s
an inner join so this is a data join which is being performed right over here
this is not data blending this is eita joining yeah and by default it is an
inner join you can keep on changing the type of join and oh when I go into my
sheet through this option by adding the data source we can’t or we have to do
only through the sheet one yeah data blending is possible only by that method
because when you add it in your sheet your primary a data primary and
secondary data sources are fixed over here okay and a join is being created
between both and when you move into your sheet there’s also a change in how your
dimensions and measures are being displayed okay but in our case when we
tried to perform data blending we had two different data sources mentioned in
over here itself and each data source has its dimensions and measures
separately so it wasn’t combined so this is the basic difference between
so it is all up to you if you want if you feel fine with data join if you feel
fine with your primary and secondary data source being fixed you can very
well go on with this option and if you feel you want to toggle between your
primary and secondary data sources you want to keep changing that you can
choose data blending option so since initially we do not have a way
to join tables from different data sources we had the concept of data
blending so right now we have data joining as well as data blending with a
few differences so whichever you prefer you can very well go forward with it right so I’ll just remove this second
coffee sales and go into my sheet okay I’ll have my sheet over here and
then I will try to add the second data source which is the coffee shop so now I
am going to tell you how to edit a relationship between these two data
sources in case we do not have a common field between them right so all you have
to do is go into data go to a menu bar click on data and you can add a new data
source with this option as well okay and you have something called edit
relationship over here okay and this tells you this tells you that at at this
point of time coffee shop sales is being selected right so that is being selected
so that is the information which this tells you and you can edit the
relationship and when you try to edit the relationship you have this
relationship dialog box it tells you relationship determine how Delta from
secondly data sources are joined with primary data sources right and here you
can change your primary and secondary data sources as per your desire okay and
as you right now coffee shop sales is the primary data source because I have
selected coffee shop sales okay it is being you know if I have selected coffee
shop sales it assumes that I am going to use the fields over here and it just
tells me that since you have selected coffee shop sales it is being mentioned
as the primary data source if I change to office sales this secondary data
source over here will automatically be changed okay
and automatically state is the key or column with which a data blend is being
created right and if I say custom so I can manually add so this these are the
fields which belong to my primary data source and these are the fields which
belong to my secondary data source as per the information that I have
mentioned over here right so now I’ll say market as you can see in the excel
files I hope you remember the market from my primary data source is equal to
region from my second data source though the column names are
different the content within these columns are just the same right so if I
when I click OK there is a manual relationship that I have been created
ok market and region is the way by which now the there are two
columns now okay the state is the automatic connection or the automatic
column which was common already in both but in case if we do not have this we
can edit the relationship in this manner right so right now we’ll have state
which is by default common in both okay and now we will try to see how to use a
calculation inside after you blend your data right okay so now as we were
discussing about data blending we will now see how to perform a calculation how
to include measures from multiple data sources in a single calculation and how
did it leave the necessary information from that right so we have two data
sources the coffee shop and office sales right now okay so coffee shop sales it
has four different states okay and where is my office sales has three states
right so I’ll choose my coffee shop it has more number of states right so I’ll
choose coffee shop as my primary data source okay so I am bringing the state
of coffee shop sales into the columns yes so I have chosen the state column
the state dimension from my coffee shop sales so by this my coffee shop sales
data sauce becomes the primary data source right after that I will have the
coffee sales measure in my rows okay and I’ll go to office sales I’ll bring my
office sales measure into my rose as well right so if you want I can wrap it
up okay as you can see we have four different states okay from the coffee
shop data sauce and we have the corresponding sales and similarly since
it is a left outer join only the matching states from my office
sales which is the secondary data source only the matching States values are
displayed and the others are displayed with a null value now I would like to
create a calculation named as total sales so that calculation should display
the total sales done in these states in both coffee say in both this data source
as well as this data source so I want to add up the sales of both these
measures and I want that value to be displayed in my total sales calculation
right so how do I create a calculated field you have a small rub down arrow
right next to dimensions just click on that you can create a calculated field
with this option over here okay and you just name your calculation let it be
total sales right and now the calculation is nothing
but it’s just the summation of my coffee sales and my office sales right so right
now we are inside the office sales right so I will say some of
office sales okay since this office sales because belongs to the data source
that we are right here okay and when you try to say some of
Coffee sales now as you can see since coffee say
sales does not belong to the you know datasource that we are working on right
now it belongs to the primary data source we have this you know cost the
name of the data source and then we have the name of the measure right so
similarly if we try to create a calculation inside our primary data
source let’s see what happens okay you can create this calculated field in any
let it be your primary or secondary data so there’s gonna be no change okay so
now right now we are in a primary data source and I’m creating a calculated
field say total sales okay and over here you have your sum of coffee sales which
belongs to this particular data source and your sum of office sales which will
be displayed along with the data source name right as you can see over here okay
so now there’s an extra sum I hope no it still contains an error we have an extra
closing brace over here I think it should be fine now yes the calculation
is valid so we are just summing up the coffee sales and office sales which
belongs to this particular data source so this is the calculation that we have
made inside the calculated field right so just click on apply and okay and once
you created a calculated field it will be displayed right here under the
measures pane with an equal to hash symbol and this is the symbol for your
calculated field right so now what I’m gonna do is I’m gonna bring this
calculated field right next to the sales measures in my columns right so now as
you can see my total sales when you place the tooltip somewhere over here so
this gives me the information about the Kerala State the office sales is 2400
you know off coffee sales thousand three hundred and the total sales it is just
adding up the values of both the sales right but there’s a small fault in this
when I say total sales I should get the value of MP and Punjab as well over here
now why are why is this being displayed as null okay because whenever an integer
value is you know added to null null is being displayed so we want to make a
change in our calculation by which though we have null values just give me
the actual values in case there are any during the summation process right so
I’ll just make a small change in the calculation after which we will be
getting the sales of MP and Punjab as well in our total sales so that is what
I want to happen when I say total sales so I’ll just remove this from my view
now okay I’ll again go into my total sales click on this drop down arrow okay
click say edit okay so now there is a small change that I’m going to make okay
so I’ll just use the function called Z n so this Z n is nothing but the zero null
function okay so when you have a null okay that will be
converted into zero and during the summit your summation process if you
have any actual values it will display the actual value and it will not display
the null itself right so let’s see now what happens okay so we’ll just see what happens and
I’ll come back and explain okay so now we’ll try and place this over
here yes so now as you can see I’ll just go into this again okay so now as you
can see since my office sales had null values
I used the zero null function in my office sales measure during the
calculation because I wanted to change the null values of this particular
measure as zero so that during the summation process my the values of my
other measure are actually being displayed okay so this is the small
change that I’ve made I’ve added the zero null function okay and as you can
see just when you place your tooltip over here it tells you that this
information is regarding the state of Punjab there’s of no office sales being
made and the coffee sales is 880 and the total sales is 880 as well so as you can
see the coffee sales for Punjab is 880 so this value is being displayed in your
you know when your total sales as well and this you know null values over here
it corresponds to this place over here okay it is just telling me on the whole
in my view there are two null values and it is talking about the null values
right in my office sales so please do not confuse that since it is placed next
to my total sales these null values indicate that there are two null values
in my office sales right so this is how you can use calculations when you are
blending tables from two different data sources as well okay and this
calculation can either be in your primary data source or if you want to
create your calculation in your secondary data source you can do that as
well there is no change that is going to be made right so we will go into a
primary data source where we have the calculation and now I’ll just try to
swap it okay we have a vertical bar chart over here and
I’ll just try to label them so that you will have the idea of what are the
values of each particular you know bar chart over here so when I try to label
them if I label the total sales okay so all my you know bar charts over here
we’ll have the value of only the total sales now why is this happening I want
the total sales to be labeled only over here
I want office sales to be labeled over here and I want coffee sales value to be
labeled over here now how do we do that as you can see you have three different
bar charts over here so the first one corresponds to your coffee sales okay
the second one corresponds to your office sales and the third one to your
calculation total sales right so go into your coffee sales so right now we are
inside coffee sales bar chart now bring in your coffee sales inside label so
only your coffee sales are being given the actual label then go into the office
sales bar chart okay this is the type of chart and it’s my office sales go into
your office sales data source bring your office sales into label right so this
gives the labeling of my office sales and finally go into total sales and then
go back and bring in your calculation over here inside label so I think the
labeling is appropriate now okay you’ll have a better understanding and once the
user you know sees this chart they’ll have a clear view of what you know is
being displayed in this particular chart right and you needn’t go and have a look
at your tooltip all the necessary information is displayed right away sure
okay so this is how you perform a calculation in data blending okay right
so after data joins and blends okay we have we are moving into a new topic now
so after this we are moving on to a new topic about something called
auto-generated fields for that purpose I’ll just close this
will come back we can very well you know just
edit the data source we can change data source inside tableau itself but just to
you know make things familiar I’m just you know repeatedly opening tableau and
connecting it so that you will get used to you know how it is being done so
you’ll just get used to the environment that’s why only after you drag a
particular table or sheet in your canvas area you can go into your sheet ok else
you will not be able to move into your sheet ok so right now we are back to our
sample superstore data source here and as you can see we have under our
dimensions and measures we have a few fields which are not available in our
data source and which are italic in you know text like you have the measure
names you have latitude longitude number of records and measure values so these
five fields are known as the auto-generated fields so this is
something which is by default created when we connect our data to tableau
right if we do not have any geographical you know geographical field which
belongs to our data source we will not have the longitude and long with
latitude and longitude being visible over sure right so now why do these
fields are present over here and what was the use of these fields right so
we’ll just see one by one we’ll start with the number of records okay which is
placed under the measures pane okay we have measure names inside dimensions and
we have all the other four inside measures okay so first we’ll start with
number of Records so as you can see it’s a generated feel that counts the number
of rows okay it’s an auto-generated field so now what is the use of this
number of records so just bring this number of records and place it inside
this text so as you can see it displays the total number of rows which are
present inside this orders sheet okay so it has the total number of records as it
tells you it counts the number of rows present in this particular sheet right
and with the help of this you can just see how these number of fields or number
of rows are being distributed when I mean when I say that what I mean is
let’s say I’ll have my market or region over here okay
I’ll just bring my region in rows so as you can see my nine nine nine for the
total number of rows are being distributed in this way among all the
four regions that are available right similarly I can also have let’s say ship
mode when I bring it into my rows so I have four different ship modes my
first-class same-day a second-class standard class for different ship modes
and the number of rows are being divided in this way you know among this against
this particular dimension right so you can easily find out the total number of
rows inside your table with the help of this
number of Records auto-generated field right so and if you want to you know
verify whether it is exactly showing you the total number of records by as it
showed initially the nine thousand nine ninety four you can very well try and
verify that just go into analysis in your menu bar okay click on totals and
say show column grant opens so as you can see this was the same number as your
as we had in our data source right your orders table had those many number of
rows yes so this is one way by which you can
use the total number of records you can find out in what way you’re you know
total records are being distributed let’s say my category okay so this is
the way and the grand total is also being displayed right so this is the use
of the first auto-generated field which is nothing but the number of records
okay and then we have something called measure names and measure values so now
what are these measure names and measure values okay so these are not from your
original data source right Tablo has created these automatically so that you
can build certain types of views that involve multiple measures so in case you
have a view in which you want to compare the profit sales and quantity at the
same time in a single view you can use this measure values instead of choosing
you know each measure from your measures pane so this measure values will contain
all the values of your measures so as the name tells you it contains all the
values of your measures okay and measure names is nothing but it will contain all
the names of the measures and why is it in a discreet
why is it under dimensions because it is of string type so it is discrete in
nature and that is why the names of my measures okay my measures are nothing
but discount profit quantity and sales okay all the names of my measures will
be stored in my measure names and all the values of my measures will be stored
inside measure values so I’ll just show you that if I bring measure names in my
filters as you can see these are the different measures which are you know
available right here and number of records is my auto-generated field where
latitude and longitude belong to a different data type so that is not
included okay so if I want to include all these in a view I can very well do
that with the help of this single auto-generated field over here right
that’s the purpose basic purpose of why we have these two right here okay so
I’ll just show give you some examples okay we’ll try to bring it in our view
and let’s see in what way the view can be changed with the help of these
auto-generated fields right so let’s say we have did we have a date field okay order date
which is of date datatype I’ll bring this date field in my columns or rows
anything okay and let me have my say anyone measure let’s say sales okay and
as you can see there’s a line chart which is being created okay so the
automatic chart when you have one date dimension and one measure is the
automatic I mean the line chart is the automatic type of chart which will be
created we will go through all the combinations over here and all the
automatic charts that will be created with different combinations right so
right now we have a date field a date dimension and a sales which is a measure
and we have a basic line shot right so now what will I do if I want to compare
profit along with my sales and I want so now right now two line shots are being
displayed right so now if I want both these to be displayed in a single
shot I want to compare both these lines in a single axis how do I do that right
so and I want to include discount as well okay there are three different line
shots but I don’t want this view I want a single X Y axis and all the three
lines in the same view in a single view right so now what do I do that so
instead of you know bringing all these here you can just bring your measure
names inside your filter and say I want okay I want only sales profit and
discount okay click on apply and okay so right now I have filtered my measure
names I am including only sales profit and discount okay so now when I bring my
measure values in my rows okay there’s some change that is being made okay we
don’t have a proper line over here this is because we have to go to yes and just remove this okay
we’ll have a measure values okay we’ll have a measure values right now inside
filter okay first I’ll tell you how to create a combined chart with two
with two measures and then we’ll go on to three measures right so first we’ll
go with two measures so we have an option without using measure names and
very values which is known as the dual axis when we have two measures you can
use this dual axis option right see as you can see you have your say in the
side you have your profit this side and you have your color legend so you as and
you can see a structure structure change over here right you have your sales and
your profit and there is a vertical structure change which tells you that
you have created your dual axis chart okay both your lines are being view
visible in a single chart so by this you can compare both these measures you know
single way right so now how do we do this when we have three different three
different measures right we will just see that
okay I’ll just remove these two now as we told I’ll go into my measure names
I’ll select only my sales my profit and my discount okay
and I’ll say apply and okay right now now I have my measure names inside my
filter right and I have chosen only through three are different measures so
now what I do is I bring my measure values in my rows okay and now I would
like to color it so there’s a chart there’s a mixture of all these three you
know values so I would like to color them up I’ll bring my Marsh measure
names in color okay so now as you can see the lines are being separated so
there’s you know different colors given for each measure okay and if you want
you can also bring your measure names you know for a better understanding
inside your label so it tells me that you can very well identify the lines
with the help of this color legend as well if not you can also label them so
this tells me that this is the line of sales this is how my sales is being
increased in in these particular years and this is how my profit is increased
and this is all about my discounts which is just for an example purpose how to
you know include more than two measures when you have two measures you can go in
for dual access option when you have more than three measures or if when you
want to add if you want you can keep changing you can edit the filter you can
include your quantity as well okay and you’ll have four different lines now
and there are different colors you know mentioned over here so this is how this
is where your measure names and measure values are used basically right so I
hope this autogenerated feels about number of Records measure names and
measure values were clear okay so right now till we go into a mapping session so
these three auto-generated fields will be used in our examples as well okay so
I hope what these fields are used for and what do they contain is understood
now right okay so after this measure names measure values and number of
records we have something new we are going to see how to create something
called a hierarchy and how do we create folders right and before that we will
just see you know how to manage metadata inside your sheet you can also rename
your fields inside your sheet okay just as we did in our data source page you
can very well do that just slowly double click you know I mean
I’m sorry you can either slowly double click this
or you can very well go into this and you can rename this particular field
okay you can do that you can show and hide any fields you know with the help
of this just as we did in our data source sheet okay and let’s see how to
create a hierarchy now okay so now what is a hierarchy so for example if I have
something called category okay and I like to have all the information related
to category in one place so by this you know searching for a particular
information or a particular field and navigation is very easy when we create
hierarchies when we have you know so many number of fields when we have n
number of fields where you have to go in search of every field so
when you create hierarchies like you know all the fields related to customer
like customer ID customer name in a hierarchy you can have your country city
state region all these under one hierarchy you can have your category
your product name your subcategory your product ID all these under your you know
products hierarchy so you can very well do that this is just you know for you to
it just makes easy for navigation and searching for any particular field is
made easy that’s it so that is why we generally create a hierarchy and usage
of this hierarchy in your view is also better and easier ok let’s just see that
now right now we have category over here now how do you create a hierarchy you
just click on this drop-down arrow next to your fields name you can just say
hierarchy create hierarchy okay or you have one more option just so whichever
field you want to be placed in under this just drag this subcategory and
place it on top of category and it tells you create a hierarchy and by default
the name of the hierarchy will be all the fields that are right now present in
your hierarchy right so we can just give some random name say category
information ok so and just say ok and a hierarchy is created this is the symbol
for hierarchy and have my category and subcategory ok and you can save your
space under dimensions by creating hierarchies as well right so when you
click on this it just shows what are the different fields present under this
particular hierarchy now how do we use this inside the view so just drag this
hierarchy itself in your view and as you can see
okay I’ll just stop place it in my rose let it be in columns and I’ll have my
sales so right now as you can see there’s a plus symbol over here this
indicates that this particular dimension is a hierarchy okay and when you click
on this you will get the next field which is being available in this
particular hierarchy right so if I want I can analyze the sales regarding the
categories and with one click instead of bringing sub searching subcategory and
bringing it all into my view I can just use this plus I can and then I have
still a field which was in my hierarchy right if we had another filled in this hierarchy let’s say if I
have my any let’s say the product name if I want it to be placed inside the
hierarchy as well okay as you can see I can change the order okay I want product
name to be the last so I can create such an hierarchy as well so when I try and
drag this hierarchy over here I’ll have these symbols okay and you have
different products names under each subcategory as you can see over here
right so yes so this is where you can just again
drill it up okay and this is the basic way of how you create and how useful
your hierarchy is in your view okay and we have default hierarchies as well our
date field over here okay is a day as the default hierarchy let’s see that so
when you place date over here okay and as you can see this we did not create a
hierarchy bless but I mean by but by default we have a plus symbol over here
indicating that it is a hierarchy so when when you just click on this plus
sign you get the corresponding quarters for each particular year and again when
you click you get the corresponding months under each quarter okay and then
again you will have the day the days of each month under each quarter under each
year right so this is the default hierarchy the date field is by default
as a hierarchy that we have in tableau right so this is how you create a
hierarchy and similarly you can remove your hierarchy just by clicking on this
drop-down arrow and say remove hierarchy and your fields are placed back in their
places right and so this is all about how to create a hierarchy and then we
have something called creating a folder okay so now how do you create a folder
so now I would like to create a folder okay yeah just just somewhere some blank
space over here just a group by folder okay and then go
into let’s say my city okay I would like to create a folder okay and you have yes you after you have grouped by folder
you have to change this option and only after that you will be able to view this
create folder option of a sure right so somewhere some blank space over here you
just create a folder and you give a name for your folder so right now I would
like to create a folder or where the name say locations so it will consist
all the fields related to the locations right so and say ok and now as you can
see the folder symbol your folder is created over here but
like your I mean unlike your hierarchy you you could drag your hierarchy and
face it in your view but you cannot do that with your folder you cannot drag
your folder it is just for the purpose of you know combining all the fields
which which you know give information off which gives similar information like
as in I can also create a folder for category information I can place my
category subcategory and my product name product ID and so on inside my category
folder but one difference is that I cannot drag my folder right into my view
it is just to organize your fields into separate folders might be easier for
navigation in order to find out any particular feel you have to go into that
folder okay and just find out now how do we how do you place the necessary fields
inside your folder right for example we have a locations folder now now I want
my country inside this folder so just drag country drop it into the locations
folder drag city drop it into the locations folder drag region or postal
code all the geographic rules will place into the locations folder and we have
state ok place it into your locations folder so so if I want any information
regarding the location okay I’ll just go into this folder and choose that
particular field and drag it into my view so the order in which the fields
are placed doesn’t matter because we are not going to drag the entire location
into the view right so this is just for you to easily identify or easily search
for any particular field so you can organize this as per your
desire and requirement right so this is how you create a folder inside your
dimensions pane okay and so we have just seen how to create a folder and how to
create a hierarchy okay so now next topic that will be we will be moving
into is I tell you the different marks okay so as we were discussing yesterday
we have this column shelf over here and we have this Rochelle okay we have a
page shelf and filter shelf okay filter shelf is one big topic right
because only after we finish off the filter shelf we will be able to just
explain the page shelf right so now today we will look into this marks shelf
right what are the different marks which are available what are the automatic
marks created when we have different combinations and so on right so and all
about titles and captions as we were discussing yesterday just double click
on your title and you can keep changing your sheet name you know if you have
something like product category wise sales in your sheet you can name it
as you know as you desire or you can also insert your data source name over
here if you want to give if you want to give extra information in your sheet
title you can keep adding all these information right and if you want to
change the font as well all these are general formatting options that are
available so this is how you can change your title okay and about the captions
you can just double click on your caption and you can edit your caption
very well ok these are the two things which you can perform you which you can
you know change in order to give some extra information regarding what
analysis you have been made in your view right so now all about our marks card
okay so initially we have something called automatic so without I’ll just
remove my caption yeah so by default this T over here stands for text table
okay so right now it tells me text is the automatic
shut because you know we don’t have anything in our rows and columns so when
we start with tableau the automatic will be a text table so now as we keep on
move adding our dimensions and measures to our rows and columns
the automatic keeps changing accordingly okay
so automatic it just chooses the best view or the best mark type okay for your
data according to what you have placed in your rows and columns right so first
we have for example we have both dimensions inside our columns and rows
okay so when we have let’s say our subcategory okay and we have let’s say cat agreed
okay as you can see and you can very well fill these places with
sales okay for the different subcategories over here okay you can
have any combination but the basic rule is that when you have two dimensions
when you have rows and columns both with dimensions your automatic view will be a
text table right so this is one the first automatic view with this
combination so if you have both dimensions any to any combinations of
any two dimensions you will be getting a text table by default right as you can
see there’s automatic text mentioned over here okay so this is the first
combination next combination is that when you have just now we saw when we
have both dimensions over here the automatic is a text table now what
happens when we have both rows and columns with measures okay so I have my
sales and profit okay so when you have both
measures okay it’s the shape mark which is being automatic in nature right so
this shape tells you what it signifies what it tells you about okay so this is
the second combination so we have two dimensions it will be a text table when
we have two measures it will be a shape mark type right and the next automatic
mark type is the bar chart now how do we create when does tableau create a bar
chart okay in what combination does it does it create a bar chart so now when
we have we just now discussed about two dimensions two measures and now let’s
see about one dimension and one measure I have my subcategory which is a
dimension and I’ll have my sales which is a measure so right oh the Ottoman
archetype is a bar chart so when we have one dimension and one measure this
combination it can be you know anyway you can swap it up there is known as
three that your row should have measures and your columns should have dimensions
you can have it you know any way but your automatic mark type will be the bar
chart okay so and next we have one more combination so we so far if they seen
three combinations the next one is we have date dimension okay
and we have a measure so this just now we discussed during our
measure names and values okay so when we have our date dimension as in one of our
column or rows and one measure so the line chart is the automatic mark type
right so we just now went through two dimensions two measures one dimension
one measure and one date dimension and one measure right so these are the
automatic types and you can very well change the path for a line shot of a
shirt okay you have the line type you have the step type and you have the jump
type so these are the different paths that you can choose when you have the
line shot only when only when you have the line chart displayed in your view
you will have this path option right over here okay and let’s see about the
different I mean all the other mark types as well so we just went through
the automatic text bad line and shape okay
so now let’s see how do you create an area mark or type chart okay area is
nothing but it just shows the total values okay it’s just like a line shot
but the area below the line will be filled up with some color right that is
an area chart it shows how a particular dimension is contributing to the trend
okay and we’ll just see how to do that we
will have let’s say a measure okay and I will have dimension let’s say
we have the de dimension okay and as you can see you can have your category in
the color okay and for each particular category you have been given a color
right and this is the normal line shot now you have to change this into the area Chuck okay so now if I go into area
so this is how you change it to an area MUC so the line below each you know
every line corresponds to the category vice sales okay so and you have the area
which is being filled with color below each line so this is how an area mark
looks like right so this is also with the same combination but area is not an
automatic mark we have to manually go choose it right so this is all about the
area mark and we have the square mark so when do we use C we have the square mark
over here so now when do we use this square muck so it is generally used like
when you want to show individual data points okay your data is displayed using
squares let’s just see an example to use a square type a square mark you
should have both dimensions in your rows and columns but one should be a date
dimension okay and the next should be lets say a category okay and by default
or text will be shown because as we discussed earlier you have two
dimensions which for which the automatic Marcus text okay
so now when you try to place a measure inside let’s say profit okay I’m placing
my profit inside my measure okay and it is converted into a square mark so like
each square gives me the information about the profit for each category under
each year and you have the color legend so as the color keeps getting darker
okay your corresponding profit information is being displayed with the
help of the color okay and this is also known as a heat map right and you can
also use the square mark to create three maps as well right so we’ll be
discussing all about the different types of charts during that particular session
so right now we are just discussing about the marks okay and the next mark
that we have is the circle mark okay so it displays using filled circles as you
can see we have the circle mark over here okay and let’s see if I have two
measures so we just now discussed when we have two measures it will be a shape
the automatic mark will be shape okay and it will be an open circle so if I
change it to a circle mark it will be a filled circle so that is the you know
change that we have between the shapes and the circle mark so when I a place
let’s say I have my product name in details so as you can see for each
product name one filled circle is being displayed
right and it gives the necessary profit information and sales information for
each circle okay so this is about the circle mark and will again have the
shape marks okay we have different shapes that we can assign right we have
two measures and we have the shape mark okay so when you want to clearly see the
individual data points and also you know while viewing your category is
associated with these points you can make use of the shape mark so the
default shape is an open circle okay I’ll have the let’s say let’s have the
subcategory in detail okay by default you have the circle as the default shape
so if I want different shapes for each subcategory okay I’ll have my category
we have only three categories right so now if I want to give three different
shapes for each category all I can do is I’ll go into this shape okay and I’ll
say more shapes and I can assign a pie la it okay so let’s say you you have so many different
options available okay if this is the default
okay I’ll assign the palette and apply let’s see if my each yeah so bye-bye you know assigning my
category into shape as well my each category will take up a shape okay you
can change the shapes with this options okay you can change the shape for office
supplies into any different shape as you wish right yes so this is how if you’re
if you are placing dimension inside my shapes mark okay each member of the
dimension will be given a unique shape if you do not have those many shapes for
example we have customer names we have so many number of customer names but we
do not have sufficient shapes so during that point of time the shapes will be
repeated and in such cases use shape map is not recommended because your shapes
will be repeated right so that doesn’t give you
of appropriate information so when you have limited number of members in any
particular dimension like category or subcategory or ship mode or segment you
can go on with this shape schmuck right so these are the different marks which
are available and about the map we’ll be discussing in our map section and
pichugin chart polygons and density okay we’ll have the last five in reserved for
our to be discussed during the chart sections so these are the basic
combinations okay and the basic charts which we will be using in our examples
okay and all the other marks we’ll discuss as we move into the chart
sections graphs and charts okay so we just went through different combinations
when we when we have two dimensions it’s our text table okay when we have two
measures it’s a shape automatic mark when we have a dimension and a measure
it’s a bar chart and when you have a date dimension and a measure it’s a line
shot okay and similarly when you have a date dimension and you know another dimension or let’s say
a product category or any other dimension along with your date dimension
it becomes an area if you place your category in colors you know we just
discussed how an area chart looks like and also about the square and circle and
how to change different shapes assigned to your view okay so we discussed about
the marks and I think we’ll start with filters today okay I’ll just tell you
what are the different types of filters available in tableau and in what is the
order of operations what is the filtering order of
operations okay which is being followed we’ll just go through the theoretical
part today and just explain you how filter is being you know carried out
which filter is being executed first and the particular order in which it is
being made right so we’ll start with filters okay now what are filters okay
as you can see you have a filter shelf which is available over here and
we had already discussed a little about how our dimensions and measures work
inside filters right so what is the use of these filters why do we need them
right it just narrows the data shown in your view okay so that you can focus
only on the relevant information as per your requirement for example I might
have different ship modes okay but I would like to retrieve the information
of only the first class ship mode or only same day ship mode or anything of
your choice so during such cases instead of going through all the ship modes I
can just try and choose one particular ship mode I can filter out the others
and you know focus on only the relevant information okay and this shelf over
here it also allows you whether you need your data that you have mentioned in
your filter to be excluded or included right we have I have placed my ship mode
inside filter okay in case I have I want the information only regarding first
class I can check this box or if I want information of all the other ship modes
excluding first class I can either check the other three boxes okay this is one
way or an easier method is I’ll check the first class which I don’t want to
include in my view and I’ll go click this exclude button over here so now as
you can see the first class has been striked out which means I am excluding
the information I mean the member which has has been checked whose box has been
checked so now I will be getting the information of all the other ship modes
so this filter shelf allows me to either exclude or include
data in my view okay and whenever you try to filter a field
you can choose any filter or any measure I mean any dimension on any measure into
your filter shelf and if you have applied a filter to any particular
dimension on measure that field will be displayed inside this shelf over here
for example I have my category I am just dragging it and placing into my filter
shelf I want information only about furniture and Technology apply and okay
now my category is placed inside the filter so with this I can identify that
my category dimension there’s some filter being applied in this particular
dimension okay and we have a particular order in which the filtering is executed
okay we have five different types of filters we have extra filters we have
data so we have context filter we have dimension filter and we have measure
filter okay so what is an extract filter as the name tells you it filters the
extracted data from the data source right so and similarly what is the data
source filter data source filter it the filter will be applied right into your
data source before you before you get you know the information the data from
your data source itself okay so that is all about the data source filters
context filter what is a context filter so have dimension and measure filter so
dimension fill is nothing but a filter applied to any one of your dimension is
a dimension filter and a filter applied to any one of your measure is the
measures filter so now what does this context feel is though what is it all
about so sometimes a might be a scenario where you have two dimension filters or
to measure filters or any two filters of the same type
right so I’ll have my category being filtered I want only technology
information and similarly I’ll have my ship mode
also inside my filter I’ll need only my first class and second class okay so
when you have you know more than two I mean more than one two or three
different types of filters inside your filter shelf now how does this kit
execute it so we have the order of execution okay or the order of
operations in which filter is being executed so first the extract filter
will be executed any filter that you have applied that your extract will be
executed then any filter that you have been applied to your data source will be
executed then we have something called context filter and then the dimension
filter and then finally we have the measure filter but in this case we have
two dimension filter so now which mention filter will be executed first
right you we tableau will get confused and it will provide a completely
different view which we do not expect right because I want the category to be
filtered first and then under this technology category that I have included
in my view I want the ship mode to be filtered but tableau considers both
these filters as the dimension filters itself the order in which your filters
are deserve Isabelle I mean the order in which your dimensions are visible in
this shelf does not play a role like what I’m trying to say is since I have
my category on top and then I have my ship mode it doesn’t mean that category
filter will be executed first and after which ship mode filter will be executed
tableau considers both as dimension filters and they will be executed at the
same time now in order to solve this problem okay in order to solve this
confusion we will assign one dimension filter as the context filter so by doing
that we are telling according to the order of
operations the dimension filter will be executed only after the context filter
so in this example I will change my you know dimension filter I’ll say add the
context by doing this okay there is a color change which means this is my
context filter this will be executed first and then my ship mode which is my
eye dimension filter will be executed so these are the order of operations and
this is what we can do when we have you know a problem when we have two same
similar type of filters we can tried using this option in order to avoid
confusion right and these are the different types of filters and we’ll
just see how to use filters okay and all about these extract datasource filters
context dimension and measure now I’ll just tell you what is all about internal
and external filters okay so if I have say my segment in my filter right I have
three different segments I want only Home Office and consumer to be filtered
and not excluding it I am including Home Office and consumer okay I’ll click
apply and ok now I am going to bring my segment in my columns okay and I’ll
bring my profit inside rows so as you can see it has been filtered the segment
my corporate segment is not being visible over here okay so we have
removed one segment type from the view by filtering segment dimension okay and
you can also try to you know show the filter
you can you know show us filter and by this you have created an in filter the
user themselves can change the filtering options okay
so you can either create a filter for any dimension by dragging it inside the
filter shelf okay or else you can also choose this drop-down option over here
and you can say you can you know there will be an option since I have already
filtered you can choose the filter option from this drop-down box or it is
always better you just drag it into your filters shelf okay and so now we have
segments inside of you inside of you in the sense segment is a dimension which
is placed in either the row and column and we are filtering the view in terms
of a dimension which is already present in our view so this is known as an
internal filter right so when your dimension or measure is a part of the
view itself okay it is known as an internal filter now what do you mean by
external filter okay so if I want I’ll just remove this okay so now I have my
segment and profit no filters right so now if I want to see the profit for any
one particular category of products okay though my category is not a part of the
view so right now I have only my segment and profit in my view okay I’ll just
drag my category into filter shelf I’ll say only technology or only furniture
any one option and I’ll apply there’s a change in the bar chart over here okay
so my chart has been changed according to the filter that I have applied it’s a
category filter as a dimension filter but my category is a dime it’s not
present inside the view right though a present in the view I have used it to
filter the information which is being displayed in the view now
this is known as an external filter so when you have your dimension in your
view and you’re trying to filter that dantian it becomes an internal filter
and when you try to filter out the information in your view with a
dimension which does not belong to your view itself it becomes your external
fill right so this is all about your internal and external filter okay and as
I already told you filters are totally independent right the order of fields in
your filter shelf they will never affect the view right so this is about the
internal and external filter okay and I’ll just tell you about the tabs which
are available we’ll just have a brief introduction about those tabs today okay
so I’ll have my subcategory inside filters so now as you can see we have
four different tabs we have the general tab we have wild card we have condition
and top okay so general is nothing but you have three options you have to
select from a particular list you have the list of all the subcategories in
this dimension you can keep choosing from the list you can enter you know
particular subcategory name in order to search it or you can select all the
values or select none of the values with these options similarly you have custom
value lists you can manually type in your oh there are subcategories to be
filtered out or included or exclude from the filter okay you can manually type in
the subcategories over here and use all will automatically use all the
subcategories present inside the filter option I mean if a present inside this
particular field ok so this is all about your general tab and you have a summary
of what are the filters the filter options that you’ve been used so far so
the field name or you have selected 0 of 17 values and
it keeps changing as you keep selecting ok and this is about the general tab
okay and your wildcard tap your wildcard tab
is nothing but you can filter using these four options mentioned over here
right so for example I have subcategories containing let’s say it’d be l.e so this is something that my
sub categories contain right so if any of my sub category name contains this
this you know four alphabets over here okay this particular text over here this
string if any of my sub category contains these strings it will be
displayed in my view let’s just try that click on apply and okay so right now
we’ll just clear the sheet okay I’ll have my subcategory okay yes I’ll again
bring it to my filters I’ll go into wild card and I’ll say this is the text apply
and okay now when I bring my subcategory in my view
okay so tables is the only subcategory with a string that I had mentioned so
when I remove this filter I have all these subcategories okay let’s try one
more I’ll say if my has a and B together so that text together what happens and
go into wild card tab and say a B apply and okay now we have only labels and
tables okay which shall a and B string so with it you can also filter out the
information using this these options as well right and similarly we if something
called starts bit so whichever alphabet your you want the subcategories to be
displayed which starts with any particular alphabet let’s see
okay starts with a apply and okay and as you can see all the subcategory starting
with a is displayed similarly you have something called ends with ends with
let’s say s apply and okay although subcategories which ends with s you know
are displayed over here and similarly the last one that we have is exactly
matches so now I should type in agree I mean a sub cat name which exactly
matches if I say table apply and okay there’s nothing that is
going to be displayed because it should exactly match my subcategory name so
when I say tables so this is when this particular subcategory will be displayed
okay this is all about your wildcard tab right so and we have something called
the condition tab so by field so this I can assign a condition by which my
filter is to be performed right I can choose any particular fields let’s say
by sales an aggregation can be chosen from these options okay and your sales
you can just use this load option over here to load in the minimum and maximum
values of my sales of my sum of sales right so with the help of this these
minimum and maximum values you will have an idea as in please filter out or
please display only those sales which are you know greater than
let’s say around 50,000 so with the help of this minimum and maximum value this
just gives me the range of values of my sum of sales for me to decide on what
value I can mention over here in order to filter it out okay so now this is
just the same if I say by formula I will be typing in the exact formula sum of
sales greater than 50000 inside this formula box so both works the same way
right and we have something called the top tab so if I want to filter out the
data let’s say I want to see the top 10 sales by sum of sales okay
and I’ll say apply okay I should choose this okay none over
here and I’ll go to my top and I’ll say top ten by some off sales okay
just apply and okay so right now I have my subcategory and I’ll have my yes I think I’d remove the filter I’m
sorry I should just apply a filter top ten by
I’ll have my sales okay so as you can see first and sort it out and I’ll I
want to display only the top ten or let’s say only the top five now how do I
do that I’ll bring my subcategory inside filters go to top by field top ten by
the sum of sales so just click on apply and okay you will be displayed only the
top ten sales that is why I sorted out in a descending order so only the top
ten by the sum of sales measure will be displayed in your view right you can
also try and change this you can also say as bottom ten so the least ten
subcategories by sum of sales will be displayed right so this is how you try
to filter out using the different tabs available in the filter shelf hour or
the filter dialog box right so this brings us to the end of the session I
hope now you have a clear understanding about tableau if you have any doubt or
query related to W do comment it on the comment section given below and if you
want to become masters in tableau do check the link given in the description
box thank you for watching the video see you soon

18 Replies to “Tableau Training for Beginners | Tableau Tutorial | Intellipaat”

  1. Guys, which technology you want to learn from Intellipaat? Comment down below and let us know so we can create in depth video tutorials for you.:)

  2. You don't need to advertising your channel, because your content is very good and helpful for students.
    Thank you

  3. Can you please make a video on advanced topics, such as, LOD Expression, Time Series Analysis, Forecasting, Calculation and Statistical Functions. Please make one full in detailed videos on this topics.

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  5. hi….. i cant get that "SHOW ME" option when i m trying to understand the "MAP" part.. i m using 2019.2 version. please help me out with this issue.

  6. content is good undoubtedly. but she stretched the video unnecessarily, people may loose interest. She is repeating lot of thing multiple times. For example, she mentioned "union works vertically and joining works horizontally" at least fro 7 to 8 times in 2 minutes. I guess, this video may complete withing 2 and half hours. Only due to lot of repeated speech, it stretched very long. If my suggestion works, please try to edit the video and make it little bit short.

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