Tableau is a Business Intelligence tool for visually analyzing the data. Users can create and
distribute an interactive and shareable dashboard, which depict the trends, variations, and
density of the data in the form of graphs and charts. Tableau can connect to files, relational and
Big Data sources to acquire and process data. The software allows data blending and real-time
collaboration, which makes it very unique. It is used by businesses, academic researchers, and
many government organizations for visual data analysis. It is also positioned as a leader
Business Intelligence and Analytics Platform in Gartner Magic Quadrant.
A Tableau data extract is a compressed snapshot of data stored on disk .
Extracts are saved subsets of data that you can use to improve performance.. When you create
an extract of your data, you can reduce the total amount of data by using filters and configuring
other limits. After you create an extract, you can refresh it with data from the original data. When
refreshing the data, you have the option to either do a full refresh, which replaces all of the
contents in the extract, or you can do an incremental refresh, which only adds rows that are new
since the previous refresh.
The benefit of Tableau extract over live connection is that extract can be used anywhere
without any connection and you can build your own visualization without connecting to
database
Here is the complete list of chart types from the Show Me menu. Be sure to check back often as
we continue to release new articles in each chart type in this sub-series.
- Text Table (Crosstab)
- Heat Map
- Highlight Table
- Symbol Map
- Filled Map
- Pie Chart
- Horizontal Bar Chart
- Stacked Bar Chart
- Side-by-Side Bar Chart
- Treemap
- Circle View
- Side-by-Side Circle View
- Line Charts (Continuous & Discrete)
- Dual-Line Chart (Non-Synchronized)
- Area Charts (Continuous & Discrete)
- Scatter Plot
- Histogram
- Box-and-Whisker Plot
- Gantt Chart
- Bullet Graph
- Packed Bubbles
Q6. What is Treemap and what are the building elements of treemap ?
The tree map displays data in nested rectangles. The dimensions define the structure of the
tree map and measures define the size or color of the individual rectangle. The rectangles are
easy to visualize as both the size and shade of the color of the rectangle reflect the value of the
measure.
A Tree Map is created using one or more dimension with one or two measures.
Q7. What is Dual Axis and How do you enable a dual axis on a chart ?
A dual-axis graph displays two different axes, on opposite sides of the graph. This can
be the left and right vertical axes or the top and bottom horizontal axes. To create a dual-axis
graph, you create an area, bar, or line graph and add a metric to display on the graph’s second
parallel axis.
Q8. Tell me about all products of Tableau ?
Tableau offers five main products: Tableau Desktop, Tableau Server, Tableau Online, Tableau
reader and Tableau Public.
(i)Tableau Desktop:
It is a self service business analytics and data visualization that anyone can use. It translates
pictures of data into optimized queries. With tableau desktop, you can directly connect to data
from your data warehouse for live upto date data analysis. You can also perform queries without
writing a single line of code. Import all your data into Tableau’s data engine from multiple
sources & integrate altogether by combining multiple views in a interactive dashboard.
(ii)Tableau Server:
It is more of an enterprise level Tableau software. You can publish dashboards with Tableau
Desktop and share them throughout the organization with web-based Tableau server. It
leverages fast databases through live connections.
(iii)Tableau Online:
This is a hosted version of Tableau server which helps makes business intelligence faster and
easier than before. You can publish Tableau dashboards with Tableau Desktop and share them
with colleagues.
(iv)Tableau Reader:
It’s a free desktop application that enables you to open and view visualizations that are built in
Tableau Desktop. You can filter, drill down data but you cannot edit or perform any kind of
interactions.
(v)Tableau Public:
This is a free Tableau software which you can use to make visualizations with but you need to
save your workbook or worksheets in the Tableau Server which can be viewed by anyone.
Q9. On which Tableau version you have worked on ?
I worked on tableau 9.3
Q10. What was the new features added in Tableau version 8,9 & 10 ?
Differences between Tableau 8.3 and Tableau 9.3, 9.2, 9.1 and 9.0
Analytics :
Key addition in Tableau 9.x. Analytics tab adjacent to Data helps to directly implement the
following features:
Summarize
- Constant Line
- Average Line
- Median with Quartiles
- Box Plot
- Totals
Model
- Average with 95% CI
- Trend Lines
- Forecast
Custom
- Reference Line
- Reference Band
- Distribution Band
- Box Plot
Calculated Fields :
A major area of change. The following is the list in Tableau 9 version.
- Freeform Calculation
- Drag and Drop features
- Google like options list during formula building process has been introduced in Tableau 9
version
- Prameter creation within the create calculated fields box has been removed
- Dimensions and Measures should drag dropped or typed in the formula box
Tableau 8.3 calculated fields box allows to access dimensions and measures directly in the
same screen and provides access to create a parameter without leaving the formula box.
Performance Improvements in Tableau 9.x:
- Tableau 9.x is 3 to 4 times faster than 8.3
- Multicore Query Execution
- Persisted Query Cache
- Parallel Queries
Data Preparation Improvements in Tableau 9.x:
- Tableau 9.x allows Unpivoting
- Web Service API Connector
- Splitting of Data automatically
More Data Sources in Tableau 9.x:
- Can access STATISTICAL files from SAS, R, SPSS
- More Amazon, Google and Other sources are allowed to connect
- Cloud based data sources can be connected
- Multidimensional data sources are accessible
In Tableau 10, we’ve improved both the beauty and brains of Tableau. We’ve added dozens
and dozens of new features to make your analysis faster, easier, and even more delightful.
Here are ten features that are specifically designed to empower your entire enterprise.
1. Revision history
Roll back to an older version of a workbook with just one click in Tableau Server. And restore
older versions of your data sources by downloading and republishing them.
You can also limit the number of revisions on the Tableau Server site settings page.
2. Licensing views
Tableau Server includes new administrative views that give insight into licensing and usage of
Tableau Desktop. Once configured, Tableau Desktop sends usage information to Tableau
Server in the background every eight hours, server login not required.
3. Subscribe others
Easily share vizzes with your team. Subscribe others to your dashboard with a click. The
subscription email will include your name, so those users will know who to thank.
4. Mobile device management
We’ve added support for VMware Airwatch and MobileIron using a new industry approach
called AppConfig. This means you can securely deploy Tableau Mobile across your
organization.
5. Site SAML
On Tableau Server, you can now leverage different SAML-based identify providers on a per-site
basis.
6. JavaScript API improvements
We've added two new functions to the JavaScript API that enable programmatic access to the
underlying data in your visualizations. With
the getSummaryDataAsync and getUnderlyingDataAsync functions, you can export data for use
in other programs.
7. REST API improvements
The Tableau REST API has been expanded with more metadata information options, user result
filtering, and the ability to return your Tableau Server version.
8. Document API
We've added a new Document API which provides a supported path for working with Tableau
files such as .twb and .tds. This means you can create a template workbook in Tableau and
easily deploy that across multiple servers and/or databases.
9. Web Data Connector 2.0
Build more flexible and powerful connectors with the Web Data Connector 2.0. This version is
easier to use and also supports multiple tables and joins.
10. ETL refresh
With this feature, you can leverage our Web Data Connectors when working with Alteryx and
Lavastorm. If you’re using these products for data prep or ETL, then you can change the data-
source parameters right from Tableau Desktop.
Q11. Tableau Public vs Tableau Desktop, limitations of Tableau Public ?
Tableau desktop:
Tableau desktop is used for developing visualizations in the form of Sheets, Dashboards and
Stories. Other useful functionalities of Tableau desktop are:
Data transformation, creating data sources, creating extracts and publishing visualization on the
Tableau Server. Tableau desktop produces files with extensions twb and twbx.
It is a licensed product but comes with 2 weeks of trial.
Tableau Public:
It is a free application provided by Tableau to develop visualizations. In functionality, it is similar
to Tableau desktop but files are published on Tableau Public and are accessible to everyone.
Q12. What type os source you have worked with ?
Q13. What is Data Preparation ?
Q14. Joining vs Blending of Data ?
Join is a query that combines the data form 2 or more tables by making use of Join
condition.
Normally in the Tableau we can perform the analysis on the single data server. If we want to
perform the analysis from the multiple data sources in a single sheet then we have to make use
of a new concept called as data blending.
Data blending mix the data from the different data sources and allow the users to
perform the analysis in a single sheet. Blending means mixing. If we are mixing the data
sources then it is called as data blending
1) The difference between joining and blending data:
Joining your data can only be done when the data comes from the same source, for example
from two sheet tabs within a single Excel file. If that same information was stored in separate
Excel files you would need to do a data blend in Tableau. A blend is always required if the data
is stored in two separate "data sources" within Tableau. So even if your data is very closely
related and exists in two separate files or databases, you will have to do a data blend if you are
combining the data in Tableau.
When blending data, the first data source used in your view will dictate how your worksheet
view in Tableau is built. The secondary (blended) data source will be able to contribute extra
information, but will not be able to change the overall structure of the view. The secondary data
source's values can be aggregated and applied to the existing view after you have established a
"relationship" by assigning a variable that both the primary and secondary data sources have in
common.
2) When to use data blending:
It is generally preferable to avoid data blending when you can combine the two data sources
outside of Tableau. If this is not an option, then you must identify at least one common variable
shared by the two data sources you want to blend together. When possible, go for a join rather
than a blend. If you need to combine two data sources and for whatever reason cannot manage
to join the data outside of Tableau, your only option is a data blend.
A simple example is having (a) a data source with three columns including location names and
latitude/longitude values, and (b) a data source with location names and detailed information
about each location. You could build a map using (a) and then blend in extra supplemental
information using (b), where a relationship is built by connecting the data sources based on the
location names.
3) When to use joining:
You can only use joining when your data comes form the same underlying source (for example,
the same Excel file or Access file).
4) When are you unable to blend data from two or more sources?
If there are no variables shared between each data source then you will not be able to do a data
blend, because there is no information that can be related from one source to the other.
However, this does not mean that the column headers (variable names) need to be an exact
match. You can edit the relationships manually to point Tableau to the variables that have
matching underlying values.
For example, if I am blending information together based on countries and source (a) calls it
"Country" while source (b) calls it "Locations", I can edit a relationship manually to blend on
these two variables. If the two column headers are an exact match, Tableau may automatically
establish the link for you.
4) When are you unable to join data?
If the data comes from different underlying files you will not be able to do a join within Tableau. I
recommend preparing your data before importing it into Tableau (there are many great tools
available, one being Alteryx, that can help with this). In my opinion blending and joining in
Tableau should be a last resort for times when you are unable to shape your data into one
coherent file for analysis.
Q15. Difference between CSV & Excel ?
The difference between CSV and XLS file formats is that CSV format is a plain text format in which
values are separated by commas (Comma Separated Values), while XLS file format is an Excel
Sheets binary file format which holds information about all the worksheets in a file, including both
content and formatting
CSV files are file formats that contain plain text values separated by commas.
CSV files can be opened by any spreadsheet program: Microsoft Excel, Open Office, Google Sheets,
etc. You can open a CSV file in a simple text editor as well. It is a very widespread and popular file
format for storing and reading data because it is simple and it’s compatible with most platforms. But
this simplicity has some disadvantages. CSV is only capable of storing a single sheet in a file, without
any formatting and formulas.
XLS files are Microsoft Excel’s workbook files in use between 97-2003. Later Excel versions use the
XLSX extension. XLS and XLSX file formats contain all the information from the worksheets in a
workbook, including formatting, charts, images, formulas, etc.
Q16. How many types of Filter ?
Filter is nothing but it is restricted to unnecessary, it is showing exact data. Basically filters are 3
types.
1. Quick filter
2. Context filter
3. Datasource filter
Tableau filters change the content of the data that may enter a Tableau workbook,
dashboard, or view. Tableau has multiple filter types and each type is created with
different purposes. It is important to understand who can change them and the order of
each type of filter is executed. The following filters are numbered based on the order of
execution.
A. Secure Filters: Filters that can be locked down to prevent unauthorized data access in
all interfaces (i.e., Tableau Desktop, Web Edit mode, or standard dashboard mode in a web
browser).
1. Data source filters: To be “secure” they must be defined on a data source when it is
published. If they are defined in the workbook with live connection, Tableau Desktop users
can still edit them. Think of these as a “global” filter that applies to all data that comes out of
the data source. There is no way to bypass a data source filter.
2. Extract filters: These filters are only effective at the time the extract is generated. They
will not automatically change the dashboard contents until the extract is
regenerated/refreshed.
B. Accessible Filters: Can be changed by anyone that opens the dashboard in Tableau
Desktop or in Web Edit mode, but not in regular dashboard mode in a web browser.
3. Context filters: You can think of a context filter as being an independent filter. Any
other filters that you set are defined as dependent filters because they process only the data
that passes through the context filter. Context filters are often used to improve performance.
However if the context filter won’t reduce the number of records by 10% or more, it may
actually slow the dashboard down.
4. Dimension filters: Filters on dimensions, you can think of as SQL WHERE clause.
5. Measure filters: Filters on measures, you can think of as SQL HAVING clause.
C. User Filters: Can be changed by anyone in Tableau Desktop, in Web Edit mode, or in
regular dashboard mode in a web browser.
6. Quick filters: Commonly used end user filters.
7. Dependent quick filters: There are quick filters depends on another quick filter.
Dependent quick filterscan quickly multiply and slow down dashboard performance.
8. Filter actions: To show related information between a source sheet and one or more
target sheets. This type of action works well when you are building guided analytical paths
through a workbook or in dashboards that filter from a master sheet to show more details.
These will seem the most “responsive” to end users in terms of user experience, as they
don’t incur any processing time unless they are clicked on by the user.
9. Table calculation filters: Filters on the calculated fields.
Q17. What is Context Filter ?
o Context Filter is used to filter the data that is transferred to each individual worksheet.
When a worksheet queries the data source, it creates a temporary, flat table that is uses
to compute the chart. This temporary table includes all values that are not filtered out by
either the Custom SQL or the Context Filter.
o "By default, all filters that you set in Tableau are computed independently. That is, each
filter accesses all rows in your data source without regard to other filters. However, you
can set one or more categorical filters as context filters for the view. You can think of a
context filter as being an independent filter. Any other filters that you set are defined as
dependent filters because they process only the data that passes through the context
filter."
Q18. How do you change a Quick Filter to a drop down ?
By clicking on drop down icon present on quick filter pane we get many options to change the
filter show options
Q19. If a field is not in your view, can you use it as a filter for the view ?
Yes.
Ex. In data source I have column like
empID, EmpName, EmpDept,EmpDsignation, EmpSalary
In reports I am using empname on columns and empsalry on rows.
I can use empDesignation on Filters
Q20. How do you change the level of detail without adding to the Visualization ?
Q21. Tableau Desktop and Server limitations ?
Q22. Difference between twb vs twbx ?
A twbx is a "zipped" archive containing a twb + any external files associated with that workbook,
such as extracts and background images.
A .twbx file is a Tableau Packaged Workbook, meaning it is the original .twb file grouped
together with the datasource(s) in one package. .twbx files can be considered analogous to
specialized zip files, in which these “zip” files contain all the information necessary to work in
Tableau. The primary advantage to using .twbx files is that analysis can be performed without
network/internet connections to your data because your data is already present on your
computer in this packaged file.
Q23. What is Blended Axis and how do you create that ?
This is mainly used when more than two mesaures are used in multi lines graphs or charts. Also,
when there is a need to show two measures on the same axis, then Blended Axis is the option to
explore. We need to drag drop the scond, third and other mesaures in to the first axis of the measure
to blend the multiple measures in to one. In this case the single blended axis with multiple measures
contains the range of values from the source to satisfy all the measures those are blended in to one
axis. The name of the axis changes in to 'Value' which generic in nature.
Q24. When can you delete sheet and when can you only hide them ?
If I want to use the sheet in dashboard or story then I can hide the sheet. If I will not use the
sheet anymore then I can delete the sheet.
Q25. How do you make animations leave a trail ?
By using page shelf you can make animations.
Q26. How do you run a simple linear regression statistical model ?
Q27. How does Aggregation works in Tableau ?
Sometimes it is useful to look at numerical data in an aggregated form such as a summation or an
average. The mathematical functions that produce aggregated data are called aggregation functions.
Aggregation functions perform a calculation on a set of values and return a single value. For
example, a measure that contains the values 1, 2, 3, 3, 4 aggregated as a sum returns a single
value: 13. Or if you have 3,000 sales transactions from 50 products in your data source, you might
want to view the sum of sales for each product, so that you can decide which products have the
highest revenue.
You can use Tableau to set an aggregation only for measures in relational data sources.
Multidimensional data sources contain aggregated data only.
Q28. Table Calculation vs Calculated Fields ?
Table Calculations (including the Quick Table Calculations) live in our Tableau View. They are
created in the view and stay there, locally in our worksheet.
Calculated Fields are created on a data level and appear as a separate column in the data source.
Tableau doesn’t change the source, but can create an extract where the calculations will be visible.
Q29. Is a blend in Tableau a type of Join? If yes then which type ?
Data Blending isn't really a join, but a blend. The closest analogy is a LEFT Join, but the results are
aggregated (on the join fields you define) and then Joined on those fields. by way of example if I had
the following 2 tables
Q30. What are the filters and type ?(R)
Q37. Give an Example or use case of Data Source Filters ?
After connecting with the data, before going to the sheets. If changes are needed in data that
time we use the data source filters.
If there are null values in the data to filter the null values or any other values. That time we can
use the Data source filters.
Q32. Context Filters ?(R)
Q33. Difference between Joins vs Blend ?(R)
Q34. How do you combine data through Appending ?
Q35. How do you combine Data through Custom SQL Query ?
Q36. Static vs Dynamic Sets ?
Q37. What roles Dimensions and Measures Play in Tableau?
Q38. Discrete vs Continuous Variables in Tableau ?
