1. What is the difference between Traditional BI Tools and Tableau?

Traditional BI Tools vs Tableau

Traditional BI Tools	Tableau
1. Architecture has hardware limitations.	1. Do not have dependencies.
2. Based on a complex set of technologies.	2. Based on Associative Search which makes it dynamic and fast
3. Do not support in-memory, multi-thread, multi-core computing.	3. Supports in memory when used with advanced technologies.
4. Has a predefined view of data.	4. Uses predictive analysis for various business operations.

2. What is Tableau?

• Tableau is a business intelligence software.
• It allows anyone to connect to the respective data.
• Visualizes and creates interactive, shareable dashboards.
• Some of the advantages of using Tableau
• data analysis like data extraction, processing, representing/visualizing and sharing the final reports/dashboards/worksheets with others
•  interactive dashboards, quick responsiveness, and real-time data analysis.
• Data visualization: Rather than having complex computations over an Excel sheet, Tableau provides beautiful insights, data blending, and dashboarding derived from the data.
• Create interactive visualizations: Tableau provides a drag-n-drop facility to quickly let the users interact with the data. You can check some of the templates created using tableau in the tableau gallery. 
• With Tableau’s gallery of templates, you can choose your option and customize it. With data visualization features, you can easily embed tons of information in the form of infographics that appeals to the audience.
• Ease of implementation: With drag-n-drop options, Tableau is reportedly easier to use. This is one such tool that you can learn without having any coding background or experience in Python, Business objects, or DOMO.
• Handle large amounts of data: Tableau is competent enough to handle millions of rows without affecting the dashboard performance.
• Integration of scripting languages: With Tableau, you can perform complex data computations using scripting languages like Python and R by importing some visuals or packages.
• What are the advantages of using Tableau?
• Speed
• Ease of use
• Beautiful and interactive dashboard
• Direct connection
• Easy publishing and sharing
• Growing market share and popularity
• Q.3. What are the main features of Tableau?
• The reason behind Tableau gaining immense popularity in little time is its attractive set of features and functionalities.
• Some key features of Tableau are:
• Drag-and-drop functionality
• Range of native data connectors
• Data highlights and filters
• Share dashboards
• Dashboard embedding
• Mobile-ready dashboards
• Data notifications
• Tableau Reader (for data viewing)
• Dashboard commenting
• Creating “no-code” data queries
• Queries to visualization conversions
• Import data of all sizes
• Creating interactive dashboards
• Creating guided stories
• Metadata management
• Automatic updates
• Security permissions at any level
• Tableau Public for data sharing
• Server REST API
• ETL refresh

 What is Tableau Server? Discuss its components.

Tableau Server is a communication tool that is used in sharing visualizations and data connection information with the end-users or clients.

It is an important component in the working of Tableau because it is designed to manage and execute crucial processes.

Tableau Server consists of several components such as:

• Gateway
• Application Server
• Repository
• VizQL Server
• Data engine
• Backgrounder
• Data Server
• Search and License

Q.5. Can you explain the Tableau design flow?

The design or logic flow in Tableau is as follows:

• Connecting to the data source through the connectors available in Tableau.
• Create data views, that is, creating visualizations like charts, graphs, etc.
• Enhancing the data views using advanced Tableau methods.
• Creating different worksheets so that we can have different data views from the same or different data.
• After worksheets, we can create dashboards that are organizing different and relevant data views in a single view for reporting.
• Using these dashboards or workbooks we can create stories to express the language of data better.

Q.6. What are data extract files in Tableau?

The data extract files are the ones that contain a local copy of the entire dataset or in other words, we take a subset of data from the source.

The Tableau Data Extract files have a “.tde” extension.

They do not contain a file path or information about the data source, workbooks, dashboards, etc in them.

Tableau Data Extract files are useful as they are highly compressed and optimized to improve Tableau’s performance especially when we are using data connections that are slow.

Q.7. How to create a .tde file in Tableau?

To create a Tableau Data Extract (.tde) file we have to,

• Go to the Data tab present on the top left of the Tableau toolbar.
• Select a data source.
• Click on the Extract Data option.
• Then, either select fields from the data source or just click on Extract to create a data extract file (.tde) of the entire data set from the data source.

Q.8. What is a Tableau Dashboard?

A dashboard is a collection of different data views.

Different data views are different kinds of visualizations that we create on Tableau.

We can bring together different elements from multiple worksheets and put them in a single view on a dashboard.

In a dashboard, we can import and add charts and graphs from worksheets to create a dashboard.

Also, on a dashboard, we can place relevant charts and graphs in one view and analyze them for better insights which help in informed decision-making in business.

Q.9. What are user functions in Tableau?

The user functions in Tableau are unique functions that we use to perform operations on the registered users on Tableau Server or Tableau Online.

We use the User functions to apply user-specific filters or row-level security functions on Tableau users.

For instance, if we want to restrict a view to just one user we can do so by using one of the user functions. Some commonly used user functions are FULLNAME, ISFULLNAME, ISMEMBEROF, ISUSERNAME, USERNAME, USERDOMAIN, etc.

Q.10. What is the difference between Tableau Workbook and Tableau Packaged Workbook?

Both the Tableau Workbook and Tableau Packaged Workbook are file types used in Tableau.

The Tableau Workbook type of file contains information about worksheets and dashboards that are present within a Tableau workbook.

The Tableau Workbook files have an extension as .twb.

We can only create these files from a live data connection and share them with users having access to that live connection.

So, the .twb files contain metadata related to the existing data connection and does not contain the actual data from the workbook.

The Tableau Packaged Workbook file type is different from the .twb files as it contains both the metadata or information about the data of a workbook and the data extracted from the data source.

They have an extension .twbx.

The .twbx file type is used in place of a .twb file when you want to share a workbook with a user who does not have access to the live data connection.

Thus, in this case, your .twbx file contains data extracted from the source along with the other information about the workbook.

Q.11. What are the different data types in Tableau?

Tableau identifies and categorizes the incoming data in various categories of data.

The different data types available in Tableau are:

1. String values (Text): This data type consists of zero or more characters.

The string values have the characters enclosed in a single or double quote (as known as single or double inverted commas).

2. Integer values (Numbers): The values of this data type can be either an integer type or floating type numbers. It is a numeric data type.

3. Date & Time values: This data type consists of date and time values in different formats such as dd-mm-yy, dd-mm-yyyy or mm-dd-yyyy, etc. for date and hr:min:sec for time.

Tableau also has a separate Date data type which contains only the date values of different types like a year, month, quarter, week, day, etc.

4. Boolean values (True or False; relational): The values of this data type are in the form of True and False that is a result of relational calculations.

Therefore, boolean values are also known as logical values.

5. Geographic values (Region, Postal code, etc): The data values of this data type are those which are used in a map. It consists of values related to country name, state name, city, region, postal codes, etc that belong to the geography of a region.

This data type is denoted by a globe icon.

6. Cluster group or mixed values: This data type is assigned to the fields having values of more than one data type.

3. What are the different Tableau Products and what is the latest version of Tableau?

Here is the Tableau Product family.

(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.

4. What are the different datatypes in Tableau?

Tableau supports the following data-types:

5. What are Measures and Dimensions?

Measures are the numeric metrics or measurable quantities of the data, which can be analyzed by dimension table. Measures are stored in a table that contain foreign keys referring uniquely to the associated dimension tables. The table supports data storage at atomic level and thus, allows more number of records to be inserted at one time. For instance, a Sales table can have product key, customer key, promotion key, items sold, referring to a specific event

The measure values are the quantifiable values which we use in calculations.

Thus, all the measure values are predominantly numeric values as it is only them that are processed and calculated to give results that can be analyzed.

For instance, the sales field is a measure field as it will have a numeric value, that is, sales data that we can use in our analysis in a lot of ways like calculating the average sales, total sales, yearly sales, trends, sales forecast and much more.

Dimensions are the descriptive attribute values for multiple dimensions of each attribute, defining multiple characteristics. A dimension table ,having reference of a product key form the table, can consist of product name, product type, size, color, description, etc.

The dimension values are the values of specific characteristics or attributes.

The fields having dimension values known as the dimensions fields. We do not use them in calculations.

They only assign specific attributes to fields such as date, product, area, category, city, etc.

So, the dimension fields are descriptive fields describing what type of data does a field contains.

One basic difference between measure and dimension fields in Tableau is that dimensions are not aggregated while measures are aggregated.

Tableau’s specialty lies in displaying data differently either in continuous format or discrete. Both of them are mathematical terms used to define data where continuous means without interruptions and discrete means are individually separate and distinct.

While the blue color indicates discrete behavior, the green color indicates continuous behavior. On one hand, the discrete view defines the headers and can be easily sorted, while continuous defines the axis in a graph view and cannot be sorted.

6. What is the difference between .twb and .twbx extension?

• A .twb is an xml document which contains all the selections and layout made you have made in your Tableau workbook. It does not contain any data.
• A .twbx is a ‘zipped’ archive containing a .twb and any external files such as extracts and background images.

Q.13. What are the different types of functions generally used in Tableau?

In Tableau, we have a lot of processing and analytical freedom with the virtue of functions available.

With the help of different types of functions, we can perform a lot of analytical operations on the data.

The main categories of Tableau function are:

1. String function: These functions like ASCII, CHAR, FIND, ISDATE, LOWER, etc, are known as string functions because they work on the string values or characters to manipulate them.

2. Date function: We use date functions to apply logical as well as arithmetic operations on date values present at the data source.

Using the date functions we can manipulate the date values by changing the old values, creating new ones or searching data on the basis of specific dates.

Some commonly used date functions in Tableau are DATEADD, MAKEDATE, ISDATE, MAKETIME, MONTH, MIN/MAX, TODAY, NOW, etc.

3. Logical function: We use logical functions to perform logical or relational operations on data in Tableau.

Some commonly used logical functions in Tableau are, CASE, IF, IFNULL, ISNULL, ZN, etc.

4. Aggregate function: We use aggregate functions to apply aggregation on data values in different ways.

Some important aggregation functions used in Tableau are; AVG, ATTR, MAX, MEDIAN, MIN, PERCENTILE, SUM, STDDEV, etc.

5. User function: We use functions to manage the users registered on Tableau Server or Tableau Online.

Commonly used user functions are, FULLNAME, ISFULLNAME, ISUSERNAME, USERDOMAIN, USERNAME, etc.

Q.14. What do you understand by Data Extracts in Tableau?

The data extracts are also called the subsets of data that we extract from the main data source.

Using data extracts optimizes Tableau’s performance, speed and offers flexibility to handle large sets of data easily.

A local copy of that portion of data gets saved in Tableau’s memory when we create a data extract.

Working and managing data in the form of such extracts is much easier than having to manage the entire data from a live connection as extracts are saved offline in Tableau’s memory.

7. What are the different types of joins in Tableau?

The joins in Tableau are same as SQL joins. Take a look at the diagram below to understand it.

8. How many maximum tables can you join in Tableau?

You can join a maximum of 32 tables in Tableau.

9. What are the different connections you can make with your dataset?

We can either connect live to our data set or extract data onto Tableau.

• Live: Connecting live to a data set leverages its computational processing and storage. New queries will go to the database and will be reflected as new or updated within the data.
• Extract: An extract will make a static snapshot of the data to be used by Tableau’s data engine. The snapshot of the data can be refreshed on a recurring schedule as a whole or incrementally append data. One way to set up these schedules is via the Tableau server.

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.

10. What are shelves?

They are Named areas to the left and top of the view. You build views by placing fields onto the shelves. Some shelves are available only when you select certain mark types.

11. What are sets?

Sets are custom fields that define a subset of data based on some conditions. A set can be based on a computed condition, for example, a set may contain customers with sales over a certain threshold. Computed sets update as your data changes. Alternatively, a set can be based on specific data point in your view.

12. What are groups?

A group is a combination of dimension members that make higher level categories. For example, if you are working with a view that shows average test scores by major, you may want to group certain majors together to create major categories.

13. What is a hierarchical field?

A hierarchical field in tableau is used for drilling down data. It means viewing your data in a more granular level.

14. What is Tableau Data Server?

Tableau server acts a middle man between Tableau users and the data. Tableau Data Server allows you to upload and share data extracts, preserve database connections, as well as reuse calculations and field metadata. This means any changes you make to the data-set, calculated fields, parameters, aliases, or definitions, can be saved and shared with others, allowing for a secure, centrally managed and standardized dataset. Additionally, you can leverage your server’s resources to run queries on extracts without having to first transfer them to your local machine.

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15. What is Tableau Data Engine?

Tableau Data Engine is a really cool feature in Tableau. Its an analytical database designed to achieve instant query response, predictive performance, integrate seamlessly into existing data infrastructure and is not limited to load entire data sets into memory.

If you work with a large amount of data, it does takes some time to import, create indexes and sort data but after that everything speeds up. Tableau Data Engine is not really in-memory technology. The data is stored in disk after it is imported and the RAM is hardly utilized. An analytical database that computes instant query responses, predictive analysis of the server, and integrated data. The data engine is useful when you need to create, refresh, or query extracts. It can be used for cross-database joins as well.

16. What are the different filters in Tableau and how are they different from each other?

In Tableau, filters are used to restrict the data from database.

The different filters in Tableau are: Quick , Context and Normal/Traditional filter are:

• Normal Filter is used to restrict the data from database based on selected dimension or measure. A Traditional Filter can be created by simply dragging a field onto the ‘Filters’ shelf.
• Quick filter is used to view the filtering options and filter each worksheet on a dashboard while changing the values dynamically (within the range defined) during the run time.
• 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.

17. How to create a calculated field in Tableau?

• Click the drop down to the right of Dimensions on the Data pane and select “Create > Calculated Field” to open the calculation editor.
• Name the new field and create a formula.

Take a look at the example below:

18. What is a dual axis?

Dual Axis is an excellent phenomenon supported by Tableau that helps users view two scales of two measures in the same graph. Many websites like Indeed.com and other make use of dual axis to show the comparison between two measures and their growth rate in a septic set of years. Dual axes let you compare multiple measures at once, having two independent axes layered on top of one another. This is how it looks like:

Dual axes are used to analyze two different measures at two different scales in the same graph. This lets you compare multiple attributes on one graph with two independent axes layered one above the other.

To add a measure as a dual-axis, drag the field to the right side of the view and drop it when you see a black dashed line appear. You can also right-click (control-click on Mac) the measure on the Columns or Rows shelf and select Dual Axis.

19. What is the difference between a tree map and heat map?

A heat map can be used for comparing categories with color and size. With heat maps, you can compare two different measures together.

A tree map also does the same except it is considered a very powerful visualization as it can be used for illustrating hierarchical data and part-to-whole relationships.

20. What is disaggregation and aggregation of data?

The process of viewing numeric values or measures at higher and more summarized levels of the data is called aggregation. When you place a measure on a shelf, Tableau automatically aggregates the data, usually by summing it. You can easily determine the aggregation applied to a field because the function always appears in front of the field’s name when it is placed on a shelf. For example, Sales becomes SUM(Sales).  You can aggregate measures using Tableau only for relational data sources. Multidimensional data sources contain aggregated data only. In Tableau, multidimensional data sources are supported only in Windows.

According to Tableau, Disaggregating your data allows you to view every row of the data source which can be useful when you are analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine what age participants were most satisfied with the product.

Aggregation of data means displaying the measures and dimensions in an aggregated form. The aggregate functions available in the Tableau tool are:

• SUM (expression): Adds up all the values used in the expression. Used only for numeric values.
• AVG (expression): Calculates the average of all the values used in the expression. Used only for numeric values.
• Median (expression): Calculates the median of all the values across all the records used in the expression. Used only for numeric values.
• Count (expression): Returns the number of values in the set of expressions. Excludes null values.
• Count (distinct): Returns the number of unique values in the set of expressions.

Tableau, in fact, lets you alter the aggregation type for a view.

Disaggregation of data means displaying each and every data field separately.

8. What are the different types of joins in Tableau?

21. What is the difference between joining and blending in Tableau?

• Joining term is used when you are combining data from the same source, for example, worksheet in an Excel file or tables in Oracle database
• While blending requires two completely defined data sources in your report.

22. What are Extracts and Schedules in Tableau server?

Data extracts are the first copies or subdivisions of the actual data from original data sources. The workbooks using data extracts instead of those using live DB connections are faster since the extracted data is imported in Tableau Engine.After this extraction of data, users can publish the workbook, which also publishes the extracts in Tableau Server. However, the workbook and extracts won’t refresh unless users apply a scheduled refresh on the extract. Scheduled Refreshes are the scheduling tasks set for data extract refresh so that they get refreshed automatically while publishing a workbook with data extract. This also removes the burden of republishing the workbook every time the concerned data gets updated.Data extracts are the subsets of data created from data sources. Schedules are scheduled refreshes made on extracts after publishing the workbook. This keeps the data up-to-date. Schedules are strictly managed by the server administrators

23. How to view underlying SQL Queries in Tableau?

Viewing underlying SQL Queries in Tableau provides two options:

• Create a Performance Recording to record performance information about the main events you interact with workbook. Users can view the performance metrics in a workbook created by Tableau.
  Help -> Settings and Performance -> Start Performance Recording
  Help -> Setting and Performance -> Stop Performance Recording.
• Reviewing the Tableau Desktop Logs located at C:UsersMy DocumentsMy Tableau Repository. For live connection to data source, you can check log.txt and tabprotosrv.txt files. For an extract, check tdeserver.txt file.

24. How to do Performance Testing in Tableau?

Performance testing is again an important part of implementing tableau. This can be done by loading Testing Tableau Server with TabJolt, which is a “Point and Run” load generator created to perform QA. While TabJolt is not supported by tableau directly, it has to be installed using other open source products.

25. Name the components of a Dashboard.

• Horizontal – Horizontal layout containers allow the designer to group worksheets and dashboard components left to right across your page and edit the height of all elements at once.
• Vertical – Vertical containers allow the user to group worksheets and dashboard components top to bottom down your page and edit the width of all elements at once.
• Text – All textual fields.
• Image Extract  – A Tableau workbook is in XML format. In order to extracts images, Tableau applies some codes to extract an image which can be stored in XML.
• Web [URL ACTION] – A URL action is a hyperlink that points to a Web page, file, or other web-based resource outside of Tableau. You can use URL actions to link to more information about your data that may be hosted outside of your data source. To make the link relevant to your data, you can substitute field values of a selection into the URL as parameters.

26. How to remove ‘All’ options from a Tableau auto-filter?

The auto-filter provides a feature of removing ‘All’ options by simply clicking the down arrow in the auto-filter heading. You can scroll down to ‘Customize’ in the dropdown and then uncheck the ‘Show “All” Value’ attribute. It can be activated by checking the field again.

27. How to add Custom Color to Tableau?

Adding a Custom Color refers to a power tool in Tableau. Restart you Tableau desktop once you save .tps file. From the Measures pane, drag the one you want to add color to Color. From the color legend menu arrow, select Edit Colors. When a dialog box opens, select the palette drop-down list and customize as per requirement.

28. What is TDE file?

TDE is a Tableau desktop file that contains a .tde extension. It refers to the file that contains data extracted from external sources like MS Excel, MS Access or CSV file.
There are two aspects of TDE design that make them ideal for supporting analytics and data discovery.

• Firstly, TDE is a columnar store.
• The second is how they are structured which impacts how they are loaded into memory and used by Tableau. This is an important aspect of how TDEs are “architecture aware”. Architecture-awareness means that TDEs use all parts of your computer memory, from RAM to hard disk, and put each part to work what best fits its characteristics.

29. Mention whether you can create relational joins in Tableau without creating a new table?

Yes, one can create relational joins in tableau without creating a new table.

30. How to automate reports?

You need to publish report to tableau server, while publishing you will find one option to schedule reports.You just need to select the time when you want to refresh data.

31. What is Assume referential integrity?

In some cases, you can improve query performance by selecting the option to Assume Referential Integrity from the Data menu. When you use this option, Tableau will include the joined table in the query only if it is specifically referenced by fields in the view.

32. Explain when would you use Joins vs. Blending in Tableau?

If data resides in a single source, it is always desirable to use Joins.  When your data is not in one place blending is the most viable way to create a left join like the connection between your primary and secondary data sources.

While the two terms may sound similar, there is a difference in their meaning and use in Tableau:

While Join is used to combine two or more tables within the same data source.

Blending is used to combine data from multiple data sources such as Oracle, Excel, SQL server, etc

Q.16. What are custom data views in Tableau?

The custom data views in Tableau are views that a user can customize according to their analysis needs.

A custom data view is made from a normal data view by making some modifications in it or adding advanced functionalities and features in it.

In other words, custom views are views that represent a set of data in different ways.

Custom data views are alternate views of the same underlying data which presents a different story in every new view.

We can create custom views by making a drill-down dimension with predefined hierarchies.

In this case, every time you drill-down the next level, you will find data at a different level of granularity.

Another way of creating a custom view is by simply swapping the position of fields or dimensions in the Columns or Rows sections.

Q.15. What is data blending in Tableau? How is it different from joins?

The data blending brings data from two different data sources together in a single view or in a single Tableau worksheet.

For data blending in Tableau, there are two data sources; a primary data source and a secondary data source.

The relevant data of the secondary data source is taken and added with the main data of the primary data source and a blended table is displayed.

Blending is different from creating joins because blending only combines relevant data from different data sources, whereas joins work on a row-level and often duplicates data that is repeating in several rows.

Also, both data blending and joining create a left join between two data tables.

But the main point of difference is when the aggregation takes place, that is, when a join is created, the data is combined first and then aggregated.

Whereas, in data blending, the data from primary and secondary data sources are queried independently, aggregated, combined and then used for visualization.

So, the order of operations are different in both.

33. What is default Data Blending Join?

Data blending is the ability to bring data from multiple data sources into one Tableau view, without the need for any special coding. A default blend is equivalent to a left outer join. However, by switching which data source is primary, or by filtering nulls, it is possible to emulate left, right and inner joins.

Data blending is viewing and analyzing data from multiple sources in one place. Primary and secondary are two types of data sources that are involved in data blending.

34. What do you understand by blended axis?

In Tableau, measures can share a single axis so that all the marks are shown in a single pane. Instead of adding rows and columns to the view, when you blend measures there is a single row or column and all of the values for each measure is shown along one continuous axis. We can blend multiple measures by simply dragging one measure or axis and dropping it onto an existing axis.

35. What is story in Tableau?

A story is a sheet that contains a sequence of worksheets or dashboards that work together to convey information. You can create stories to show how facts are connected, provide context, demonstrate how decisions relate to outcomes, or simply make a compelling case. Each individual sheet in a story is called a story point.

Creating a story is effective in Tableau which is created by combining various charts to portray a plot of viewers. A story is a sheet that contains all the methods used to create those worksheets. To create a story:

1. Click the New Story on the dashboard.
2. Choose the right size of the story from the bottom-left corner or choose a custom size.
3. Start building the story by double-clicking the sheet and add it to the story point.
4. Add a caption to the story by clicking Add a caption.
5. You can update the highlights by clicking Update in the toolbar. You can also add layout options, format a story, or fit the story to your dashboard

36. What is the difference between discrete and continuous in Tableau?

There are two types of data roles in Tableau – discrete and continuous dimension.

• Discrete data roles are values that are counted as distinct and separate and can only take individual values within a range. Examples: number of threads in a sheet, customer name or row ID or State. Discrete values are shown as blue pills on the shelves and blue icons in the data window.
• Continuous data roles are used to measure continuous data and can take on any value within a finite or infinite interval. Examples: unit price, time and profit or order quantity. Continuous variables behave in a similar way in that they can take on any value. Continuous values are shown as green pills.

37.How to create stories in Tableau?

There are many ways to create story in Tableau. Each story point can be based on a different view or dashboard, or the entire story can be based on the same visualization, just seen at different stages, with different marks filtered and annotations added. You can use stories to make a business case or to simply narrate a sequence of events.

• Click the New Story tab.
• In the lower-left corner of the screen, choose a size for your story. Choose from one of the predefined sizes, or set a custom size, in pixels.
• By default, your story gets its title from its sheet name. To edit it, double-click the title. You can also change your title’s font, color, and alignment. Click Apply to view your changes.
• To start building your story, drag a sheet from the Story tab on the left and drop it into the center of the view
• Click Add a caption to summarize the story point.
• To highlight a key takeaway for your viewers, drag a text object over to the story worksheet and type your comment.
• To further highlight the main idea of this story point, you can change a filter or sort on a field in the view, then save your changes by clicking Update above the navigator box.

38. What is the DRIVE Program Methodology?

Tableau Drive is a methodology for scaling out self-service analytics. Drive is based on best practices from successful enterprise deployments. The methodology relies on iterative, agile methods that are faster and more effective than traditional long-cycle deployment.

A cornerstone of this approach is a new model of partnership between business and IT.

39. How to use group in calculated field?

By adding the same calculation to ‘Group By’ clause in SQL query or creating a Calculated Field in the Data Window and using that field whenever you want to group the fields.

• Using groups in a calculation. You cannot reference ad-hoc groups in a calculation.
• Blend data using groups created in the secondary data source: Only calculated groups can be used in data blending if the group was created in the secondary data source.
• Use a group in another workbook. You can easily replicate a group in another workbook by copy and pasting a calculation.

40. Mention what is the difference between published data sources and embedded data sources in Tableau?

The difference between published data source and embedded data source is that,

• Published data source: It contains connection information that is independent of any workbook and can be used by multiple workbooks.
• Embedded data source: It contains connection information and is associated with a workbook.

41. Mention what are different Tableau files?

Different Tableau files include:

• Workbooks: Workbooks hold one or more worksheets and dashboards
• Bookmarks: It contains a single worksheet and its an easy way to quickly share your work
• Packaged Workbooks: It contains a workbook along with any supporting local file data and background images
• Data Extraction Files: Extract files are a local copy of a subset or entire data source
• Data Connection Files: It’s a small XML file with various connection information

42. How to embed views onto Webpages?

You can embed interactive Tableau views and dashboards into web pages, blogs, wiki pages, web applications, and intranet portals. Embedded views update as the underlying data changes, or as their workbooks are updated on Tableau Server. Embedded views follow the same licensing and permission restrictions used on Tableau Server. That is, to see a Tableau view that’s embedded in a web page, the person accessing the view must also have an account on Tableau Server.

Alternatively, if your organization uses a core-based license on Tableau Server, a Guest account is available. This allows people in your organization to view and interact with Tableau views embedded in web pages without having to sign in to the server. Contact your server or site administrator to find out if the Guest user is enabled for the site you publish to.

You can do the following to embed views and adjust their default appearance:

• Get the embed code provided with a view: The Share button at the top of each view includes embed code that you can copy and paste into your webpage. (The Share button doesn’t appear in embedded views if you change the showShareOptions parameter to false in the code.)
• Customize the embed code: You can customize the embed code using parameters that control the toolbar, tabs, and more. For more information, see Parameters for Embed Code.
• Use the Tableau JavaScript API: Web developers can use Tableau JavaScript objects in web applications. To get access to the API, documentation, code examples, and the Tableau developer community, see the Tableau Developer Portal.

43. Design a view in a map such that if user selects any state, the cities under that state has to show profit and sales.

According to your question you must have state, city, profit and sales fields in your dataset.

Step 1: Double click on the state field

Step 2: Drag the city and drop it into Marks card.

Step 3: Drag the sales and drop it into size.

Step 4: Drag profit and drop it into color.

Step 5: Click on size legend and increase the size.

Step 6: Right click on state field and select show quick filter.

Step 7:  Select any state now and check the view.

44. Think that I am using Tableau Desktop & have a live connection to Cloudera Hadoop data. I need to press F5 to refresh the visualization. Is there anyway to automatically refresh visualization every ‘x’ seconds instead of pressing F5?

Here is an example of refreshing the dashboard for every  5 seconds.

All you need to do is replace the api src and server url with yours.

<!DOCTYPE html>

<html lang="en">

<head>

<title>Tableau JavaScript API </title>

http://servername/javascripts/api/tableau_v8.js

</head>

<div id="tableau Viz"></div>

<script type='text/javascript'>

var placeholderDiv = document.getElementById("tableau Viz");

var url = "http://servername/t/311/views/Mayorscreenv5/Mayorscreenv2";

var options={

hideTabs:True,

width:"100%",

height:"1000px"

};

var viz= new tableauSoftware.Viz(placeholderDiv,url,options);

setInterval (function() {viz.refreshDataAsync()},5000);

</script>

</body>

</html>

Some Additional Tricky Tableau Interview Questions

45. Suppose my license expires today, will users be able to view dashboards or workbooks which I published in the server earlier?

If your server license expires today, your username on the server will have the role ‘unlicensed’ which means you cannot access but others can. The site admin can change the ownership to another person so that the extracts do not fail.

46. Is Tableau software good for strategic acquisition?

Yes! For sure. It gives you data insight to the extent that other tools can’t. Moreover, it also helps you to plan and point the anomalies and improvise your process for betterment of your company.

47. Can we place an excel file in a shared location and and use it to develop a report and refresh it in regular intervals?

Yes, we can do it. But for better performance we should use Extract.

48. Can Tableau be installed on MacOS?

Yes, Tableau Desktop can be installed on both on Mac and Windows Operating System.

49. What is the maximum no. of rows Tableau can utilize at one time?

Tableau is not restricted by the no. of rows in the table. Customers use Tableau to access petabytes of data because it only retrieves the rows and columns needed to answer your questions.

50. When publishing workbooks on Tableau online, sometimes a error about needing to extract appears. Why does it happen occasionally?

This happens when a user is trying to publish a workbook that is connected to an internal server or a file stored on a local drive, such as a SQL server that is within a company’s network.

51. What is a parameter in Tableau?

The parameter is a variable (numbers, strings, or date) created to replace a constant value in calculations, filters, or reference lines. For example, you create a field that returns true if the sales are greater than 30,000 and false if otherwise. Parameters are used to replace these numbers (30000 in this case) to dynamically set this during calculations. Parameters allow you to dynamically modify values in a calculation. The parameters can accept values in the following options:

• All: Simple text field
• List: List of possible values to select from
• Range: Select values from a specified range

52. What are the supported file extensions in Tableau?

The supported file extensions used in Tableau Desktop are:

• Tableau Workbook (TWB): contains all worksheets, story points, dashboards, etc.
• Tableau Data Source (TDS): contains connection information and metadata about your data source
• Tableau Data Extract (TDE): contains data that has been extracted from other data sources.
• Tableau Packaged Workbook (TWBX): contains a combination of the workbook, connection data, and metadata, and the data itself in the form of TDE.  It can be zipped and shared.
• Tableau Packaged Data Source (TDSX): contains a combination of different files.
• Tableau Bookmark (TBM): to earmark a specific worksheet.

53.What are the supported data types in Tableau?

The following data types are supported in Tableau:

DataType	Possible Values
Boolean	True/False
Date	Date Value (December 28, 2016)
Date & Time	Date & Timestamp values (December 28, 2016  06:00:00 PM)
Geographical Values	Geographical Mapping (Beijing, Mumbai)
Text/String	Text/String
Number	Decimal (8.00)
Number	Whole Number (5)

54.

How do you generally perform load testing in Tableau?

Load testing in Tableau is done to understand the server’s capacity with respect to its environment, data, workload, and use. It is preferable to conduct load testing at least 3-4 times in a year because with every new user, upgrade, or content authoring, the usage, data, and workload change. 

Tabjolt was created by Tableau to conduct point-and-run load and performance testing specifically for Tableau servers. Tabjolt:

• Automates the process of user-specified loads
• Eliminates dependency on script development or script maintenance
• Scales linearly with an increase in the load by adding more nodes to the cluster

17. Why would someone not use Tableau?

The limitations of using Tableau are:

• Not cost-effective: Tableau is not that cost-effective when we compare it well with the other available data visualization tools. In addition to this, it has software upgrades, proper deployment, maintenance, and also training people for using the tool.
• Not so secure: When it comes to data, everyone is extra cautious. Tableau focussed on security issues but fails to provide centralized data-level security. It pushes for row-level security and creates an account for every user which makes it more prone to security glitches.
• BI capabilities are not enough: Tableau lacks basic BI capabilities like large-scale reporting, building data tables, or creating static layouts. It has limited result-sharing capabilities, email notification configuration is limited to admins, and the vendor doesn’t support trigger-based notifications

19. What are the various types of filters in Tableau?

Tableau has 6 different types of filters:

• Extract Filter: This filter retrieves a subset of data from the data source.
• Dimension Filter: This filter is for non-aggregated data (discrete).
• Data Source Filter: This filter refrains users from viewing sensitive information and thus reduces data feeds.
• Context Filter: This filter creates datasets by applying presets in Tableau.
• Measure Filter: This filter applies various operations like sum, median, avg, etc.
• Table Calculation Filter: This filter is applied after the view has been created.

23. What are the components in a dashboard?

The components displayed in a dashboard are:

• Horizontal: Horizontal view allows the users to combine the worksheets and dashboard elements from left to right and edit the height of the elements.
• Vertical: Vertical view allows the users to combine the worksheets and dashboard elements from top to bottom and edit the width of the elements.
• Text: All the textual fields.
• Image Extract: To extract an image Tableau applies some code, extracts the image, and saves it in a workbook in the XML format.
• Web URL: Hyperlink that points to a web page, file, or other web resources outside of Tableau

29. Mention what is the difference between published data sources and embedded data sources in Tableau?

Connection information is the details of data that you want to bring into Tableau. Before publishing it, you can create an extract of the same.

Published Data Source: It contains connection information that is independent of any workbook.

Embedded Data Source: It contains connection information which is connected to a workbook

31. How to use groups in a calculated field?

Add the ‘GroupBy’ clause to SQL queries or create a calculated field in the data window to group fields.

• Using groups in a calculation. You cannot reference ad-hoc groups in a calculation.
• Blend data using groups created in the secondary data source: Only calculated groups can be used in data blending if the group was created in the secondary data source.
• Use a group in another workbook. You can easily replicate a group in another workbook by copy and pasting a calculation

34. What is a Calculated Field, and How Will You Create One?

Calculated fields are created using formulas based on other fields. These fields do not exist but are created by you.

You can create these fields to:

• Segment data
• Convert the data type of a field, such as converting a string to a date.
• Aggregate data
• Filter results
• Calculate ratios

There are three main types of calculations that you can create:

• Basic Calculations: Transform values of the data fields at the source level
• Level of Detail (LOD) Expressions: Transform values of the data fields at the source level like basic calculations but with more granular access
• Table Calculations: Transform values of the data fields only at the visualization level

To create calculate fields:

In Tableau, navigate to Analysis>Create a calculated field. Input details in the calculation editor.
And, done

35. How Can You Display the Top Five and Bottom Five Sales in the Same View?

You can see top five and bottom five sales with the help of these functions:

1. Drag ‘customer name’ to row and sales to the column.
2. Sort Sum(sales) in descending order.
3. Create a calculated field ‘Rank of Sales’.

36. What is the Rank Function in Tableau?

Rank function is used to give positions (rank) to any measure in the data set. Tableau can rank measure in the following ways:

• Rank: The rank function in Tableau accepts two arguments: aggregated measure and ranking order (optional) with a default value of desc.
• Rank_dense: The rank_dense also accepts the two arguments: aggregated measure and ranking order. This assigns the same rank to the same values but doesn’t stop there and keeps incrementing with the other values. For instance, if you have values 10, 20, 20, 30, then ranks will be 1, 2, 2, 3.
• Rank_modified: The rank_modified assigns the same rank to similar values.
• Rank_unique: The rank_unique assigns a unique rank to each and every value. For example, If the values are 10, 20, 20, 30 then the assigned ranks will be 1,2,3,4 respectively.

37. What is the difference between Tableau and other similar tools like QlikView or IBM Cognos?

Tableau is different than QlikView or IBM Cognos for various reasons:

• Tableau is an intuitive data visualization tool simplifying the story creation by simple drag and drop techniques. On the other hand, BI tools like QlikView or Cognos convert data into metadata to let the users explore data relations. If your presentation runs around presenting data in aesthetic visualizations then opt for Tableau. If not, and might need a full BI platform then go for Cognos/QlikView
• The ease of use or extracting data details is easier in Tableau than compared to extensive BI tools like Cognos. With Tableau, your team members, be it a guy from sales can easily read the data and give insights. But with Cognos, only members with extensive tool knowledge are appreciated and welcomed.

Q.16. What are custom data views in Tableau?

The custom data views in Tableau are views that a user can customize according to their analysis needs.

A custom data view is made from a normal data view by making some modifications in it or adding advanced functionalities and features in it.

In other words, custom views are views that represent a set of data in different ways.

Custom data views are alternate views of the same underlying data which presents a different story in every new view.

We can create custom views by making a drill-down dimension with predefined hierarchies.

In this case, every time you drill-down the next level, you will find data at a different level of granularity.

Another way of creating a custom view is by simply swapping the position of fields or dimensions in the Columns or Rows sections.

By swapping the position of dimensions, we can view our data in a new way.

Q.17. What are the different field operations we can perform in Tableau?

Fields are the most important element in managing data as well as analyzing it.

All the data values are sorted and kept accordingly in the fields of particular data tables.

In Tableau, we can perform a variety of operations on the data fields like:

• Add new fields to a worksheet.
• Combine two or more fields.
• Create a calculated field.
• Make parameters from fields.
• Create a set of two fields.
• Group multiple fields.
• Search for existing fields.
• Rename or reorder fields.

Q.18. Can we create custom territories on a map in Tableau?

Yes, We can create custom territories on a map by grouping existing locations or territories together.

Do you know? We use custom territories in Tableau as a separate geographic cluster field without modifying the existing geographic fields.

For instance, if on a map of India, we have sales for different states like Madhya Pradesh, Maharashtra, Gujrat, Chhattisgarh, Rajasthan, we can group all of these to create a single sales territory which will be a custom territory.

Q.19. What are the different kinds of filters in Tableau?

Tableau offers a good range of filters that we can apply on the data for better analysis.

Filters allow us to view our data at different levels of granularity and detail.

We can exclude unnecessary data through filters and conduct our analysis on only the required data.

There are five different types of filters available in Tableau.

1. Extract filters: These filters create an extract or subset of data from the original data source.

In other words, the extract filters extract a portion of data from the whole from its source. We can use the data extract anywhere in the analysis once it is created.

2. Data Source filters: The data source filters are the filter conditions that we can directly apply at the data source level.

Using the data source filters we can apply filters on the data present in the data source itself instead of first importing it into Tableau.

3. Context filters: The context filters are used to apply a context for the data that we are working on.

Once we apply a context filter on a worksheet or workbook, the entire analysis is done in that applied context only.

4. Dimension filters: Dimension filters are applied specifically on individual dimensions present in the Dimensions section on a Tableau sheet.

We can easily apply dimension filters on the dimension fields by dragging and dropping the field into the Filter card present on the sheet.

5. Measure filters: Such filters are applied on individual measure fields present in the Measures section on a Tableau sheet.

We can easily apply the measure filters on the measure fields by dragging and dropping the field into the Filter card present on the sheet.

Q.20. What do you understand by context filters?

Context filters are used to apply context on the data under analysis.

By applying a context we set a perspective according to which we can see the charts and graphs.

For example, we have sales data of an electronic store and we want to conduct our analysis only for the corporate sector or segment.

To do this, we have to apply a context filter on our Tableau sheet. Once we add the context for the Corporate segment from the Add to context option, all the charts present on the sheet will only show data relevant to the Corporate segment.

In this way, we can apply a context to our analysis in Tableau.

Q.21. What is Quick Sorting in Tableau?

Tableau gives us the option to Quick Sort data present in our visualizations.

We can instantly sort data from the visualization by simply clicking on the sort button present on the axes of a graph or chart.

An ascending sort is performed upon one click, the descending sort is performed on two clicks and an applied sort is cleared on three clicks on the Quick Sort icon.

Q.22. What is Tableau Show Me?

The Show Me option in Tableau is one of the most important features of Tableau as it is a showcase of all the available visualizations in Tableau.

It has a variety of graphs and charts that we can use in our analysis in Tableau.

The Show Me menu has charts such as pie chart, bar graph, horizontal bar graph, stacked bar graph, histograms, scatter plots, treemap charts, whiskers plot, area chart, maps and much more.

The charts get activated in the Show Me menu according to the dimensions and measures that we select.

Q.23. What are the different kinds of formatting operations that we can perform in Tableau?

One reason why Tableau is a much preferred Business Intelligence tool is that it offers a wide variety of formatting options on its charts and graphs.

The formatting options gives a lot of flexibility to create visualizations of our choice as per our requirements.

We can format a visualization in a lot of ways like formatting the axes, changing the font, formatting the shade and alignment, formatting the borders, changing the color scheme, etc.

Q.24. What is a Tableau worksheet?

A Tableau worksheet is a single view sheet that can contain numerous visualizations.

A typical Tableau worksheet consists of elements like shelves, cards, Show Me menu, legends, filters, Data and Analytics pane, and a blank area to create the visualizations on.

Anything that we create on Tableau starts with creating a basic Tableau worksheet.

We can use one or more worksheets to create workbooks, dashboards, stories, etc.

Q.25. What is a paged workbook in Tableau?

A paged workbook in Tableau consists of different pages based on certain criteria.

For instance, if we want to see sales performance based on different regions, we can create a separate page for each region in a workbook.

In this way, a single workbook, that is, a paged workbook will show sales based on every region making the workbook more detailed and insightful.

Q.26. In what ways can you connect to a data source in Tableau?

We can connect to a data source in Tableau mainly in two ways; a live connection or creating an extract from a data source.

In a live connection, we get to connect directly to the data source via a connector.

So, the live connections are online connections. Whereas when we create an extract, data is taken offline and stored into Tableau’s memory.

Q.27. What is the maximum number of tables you can join in Tableau?

The maximum number of tables that we can join in Tableau is 32.

Q.28. What are shelves in Tableau?

The Shelves on a Tableau worksheet are demarcated areas used for specific purposes.

There are several shelves on a Tableau sheet like, Page shelf, Filter shelf, Marks shelf, Rows and Column shelf.

Each shelf has a specific purpose or functionality assigned to it that you can use to make your analysis better.

Q.29. What do you understand by groups and sets in Tableau?

Sets: Sets are subset of data created according to specific conditions or criteria.

Once created, we can use the sets in analysis. A set can have data based on a condition like sales values greater than 50,000.

Groups: Groups in Tableau refer to the group of dimensions brought together to create a category.

For instance, if we are analyzing test scores for different majors, we can create a group called Major that will contain all the majors for a test.

Q.30. What are hierarchical fields in Tableau?

The hierarchical fields are those which have data arranged in hierarchies.

Hierarchies organize relevant data on different levels. We can dive deep into data and analyze it at a finer level by doing a drill-down into hierarchical fields.

Q.31. How would you distinguish between Reference Band and Bollinger Bands ? 

Reference band: Such bands are shaded areas in a chart showing the points that fall in a particular reference area.

For a reference band, we need to set a range. Thus, from a reference band, we can set a range of reference and analyse the data points falling in that range. 

Bollinger band: Bollinger bands are unique charts which have a more specific view than the reference bands.

These bands analyse the prices and variation in prices with time for a financial commodity or instrument. Also, we can say that bollinger bands can show a moving average with time. 

Q.32. What are Histograms in Tableau? What is its use in analysis?

Histograms show or graphically represent the distribution of values in intervals or bins of equal sizes. These charts are specifically used to represent the distribution of continuous data. 

Histograms allow us to do statistical analysis of business related parameters like sales, profit, loss, quantity sold etc. Such quantities come under the category of continuous measures.

In order to create a histogram, Tableau takes the continuous measure values and places them into bins of equal sizes.

Bins are nothing but sets of value ranges like 0-5, 5-10, 10-15 and so on. The measure values corresponding to these ranges fall into their respective range.

Q.33. Explain Bar charts in Tableau. What are the different kinds of Bar Charts?

Bar charts represent data in categories by arranging it in rectangular bars. The height of each bar is proportional to the value that bar is representing.

For instance, a bar representing the value 1000 will be taller or greater in length than a bar representing the value 500. 

In Tableau, we can make different kinds of bar charts such as; Segmented bar chart, Stacked bar chart, Side-by-side bar chart etc.

1. Horizontal/ Vertical bar chart: A horizontal or vertical bar graph is a simple graph having bars of vertical or horizontal orientation.

2. Segmented bar chart: A segmented bar chart is a bar chart where a bar chart contains more than one set of bars.

Each set of bars belongs to a particular segment. For instance, we can have a sales bar graph for three or four different segments all seen in  a single view.

3. Stacked bar chart: A stacked bar chart has a single bar divided into smaller parts.

For instance, a single bar for the year 2019 can show sales for different countries or regions or cities.

We can also set a color scheme for the subdivisions in a bar as we can see in a stacked bar chart below.

4. Side-by-side bar chart: A side-by-side bar chart will have multiple bars standing next to each other for a single segment.

Instead of stacking multiple values one upon the other like in stacked bar charts, this chart places them side-by-side.

Q.34. What is the difference between Shared axis chart, Combined axis chart and Dual axis chart?

All of the three charts are related to the axis of a chart i.e. either the x-axis or y-axis. The main difference between the three of them is;

• Shared axis chart: This type of chart has a common or shared axis between more than one measures in a chart. 
• Combined axis chart: This type of chart has one common axis (x-axis) and two separate axis (Y-axis) for specific dimension and measures respectively.
• Dual axis chart: These charts have two axes for two measures. We can use it specifically when we have different measure ranges.

Q.35. What is a Heat Map?

Tableau heat map shows data values as density spots or heat spots on a map.

A heat map is also known as density heat map as it shows colored spots whose intensity and shade vary based on the number of values in a cluster of values.

More the number of values in a cluster, more dense it is and shown with a dark color on the map.

Therefore, we can use density heat maps or heat maps to analyse areas with densely or sparsely populated data. 

Q.36. What is the difference between a Motion chart and a Line chart?

The main difference between a line chart and a motion chart is, a line chart is a static and a motion chart is a moving chart.

A line chart simply shows a line connecting various data points whereas a motion chart is a moving chart that moves along every single data point showing the trail or path of a line.

Both motion charts and line charts are very useful in data analysis. 

Q.37. Why do we use a Waterfall chart in Tableau?

A waterfall chart shows the gradual transition of data values from start to end.

It represents a running total with successive increase and decrease happening in between the start point and end point. 

In a normal running total, we cannot see how individual categories are contributing to the whole or total.  

Using a waterfall chart, we analyse how each category’s positive values increase the total value and the negative values decrease the total value.

Such ups and downs lead to a resultant final value. And this is what we analyse in a waterfall chart. This allows for an insightful analysis in Tableau of how individual elements of dimensions or measures contribute  to bringing a total value of a parameter.

Q.38. What is a Sparkline chart? Why do we use it in analysis?

Sparkline charts are line charts or trend line charts that are compact and do not have any axis.

As it is used to show data trends, it is predominantly a time-series chart having a speciality to fit in small areas.

Sparkline charts are small charts that are very useful in analysis as they do not take up much space allowing you to put more information on a report.

Also, they graphically represent highs and lows of a data depicting a data trend.

Q.39. What do you understand by a Pareto chart in Tableau?

A Pareto chart is a chart that consists of both a bar chart and a line chart in single view.

The bars represent data values in a descending order and the line represents a cumulative total of all the values.

Such charts are useful when we want to show data in more than one way on a chart.

We can get to analyse data from two different perspectives i.e. bars and lines giving us different insights into data. 

Q.40. How can we create a Donut chart in Tableau?

Tableau donut chart is a pie chart with a hole in its center. That donut like hole in the center is used to show some cumulative values related to the data in the donut chart. 

We can create a donut chart by following some simple steps. 

1. To begin with, we create two aggregate measure fields.

2. Then we select the mark type Pie for the first measure field of the two. 

3. Add a set of fields to the Color, Label and Angle cards. 

4. Select Circle as the mark type for the second measure.

5. Change the color of the circle to white.

6. Add a measure field that you want to show at the center of the donut chart to the Label card of second aggregate measure. 

7. Select Dual Axis option from the Rows column for the second aggregate measure. 

8. Reduce the size of the inner circle. 

9. Our donut chart is ready. 

Q.41. How will you fix commonly occuring data quality issues in Tableau?

We can fix some commonly occuring data quality issues in Tableau by using a number of ways. 

• Renaming fields. 
• Grouping of fields together that have the same name but the names are written differently. For instance, H&M and Hennes and Mauritz are going to be the same names written differently.  
• Entering Aliases for fields where required.
• Making suitable corrections in the map when it is unable to process some geographic areas on the map. We can remove them or make changes in the map to rectify such geographical errors.
• If we are having a lot of null or invalid values, we can bunch them together with non-invalid values or correct the join that is causing the occurrence of null values.
• Make corrections at the data source if needed. 

Q.42. What is forecasting in Tableau?

Forecasting is a process of showing future trends by identifying regular patterns existing data values.

The technique of identifying regular patterns from existing data values is known as exponential smoothing. Tableau uses exponential smoothing and gives an accurate forecast graph that they can use in predictive analysis. 

Forecasting in Tableau is based on two important concepts i.e. Trends and Seasonality.

A trend is the increase or decrease in data over time and seasonality is a repeating variation in values over a determined or fixed period of time (such as weekly, quarterly, yearly, etc). These are known as seasons.

These seasonal and repeating variations are predictable giving us accurate forecasts for predictive analysis. 

Q.43. Explain how we do Reporting in Tableau?

Reporting is the process of collecting raw data from the data source, processing it, visualizing it using graphs and charts and sharing it with others to get meaningful insights from data.

Tableau comes with a lot of reporting features like dashboarding, creating stories, sharing the reports with other users.

One unique characteristic of reporting in a BI tool like Tableau is that it encourages all the users to work on the same platform, with the same dataset and the same vision to get the best possible output.

A good report ensures best results in the form of accurate data insights that are used in decision making in businesses and in other domains. 

We can create a report by some really simple steps that we can follow. 

• Open a new worksheet in Tableau
• Add dimensions and measures
• Create a visualization
• Add more visualizations to your worksheet if needed
• Create a dashboard
• Share the dashboard as Report

Q.44. What is a Sankey chart in Tableau?

Tableau Sankey charts are flow diagrams that graphically show the flow of values between different sets of data.

This chart gives multiple flow lines that intersect each other giving us a flow pattern of data values and sets. In a sankey chart, data points or nodes are connected via links creating a flow diagram for data set. 

Q.45. What are bins in Tableau? 

Tableau bins are analogous to containers that are of equal size and that store data values corresponding to the bin size.

The bins group a set of data into groups of equal size. This gives a systematic distribution of data.

In Tableau, we can take data from any discrete field and create bins. Although, Tableau users mostly use measure fields to create numeric bins.

Bins are very useful in data analysis as they provide a systematic data range that helps us organize information better and discover patterns easily. Bins are created by using calculated fields in Tableau. 

Q.46. What is Tableau Pivot? 

The Pivot feature in Tableau allows us to switch the rows with columns in a table.

For instance, let’s imagine a scenario where we have five interview candidates and we ask 10 questions from each one of them.

Now, when we create a normal table to store this data, we will have to create 10 columns for each candidate. This will make our table oddly big.

To prevent this, we can pivot the fields in the table and we have a single measure column that will store the score value for each question corresponding to each candidate instead of having ten columns of candidate score.

This is how pivoting works in Tableau as it is commonly used in cases where we want to make the data analysis and visualization easy. 

Q.47. What are TreeMaps in Tableau?

A TreeMap is a chart type used in Tableau to graphically represent data. The treemap charts show the data in a part to the whole manner i.e. you get to see how individual parts make up the whole.

For instance, if we see that the majority of sales occurred in the Phone segment in an electronics store.

A treemap chart can show you a bigger rectangle for the Phone segment and then a number of small rectangles within the big rectangle showing the sales of different brands like OnePlus, iPhone, Oppo, Samsung, Pixel etc.

In this way, treemaps represent multi-layered data in a part to the whole manner. 

It consists of rectangular boxes of different sizes. The size of the boxes is directly proportional to the data value i.e. bigger the value, larger the box.

The treemap chart is colored and it assigns distinctive colors to different sets of values. 

Q.48. What are Trend lines in Tableau? How to use them?

The tableau trend line shows or reveals unique patterns in data. Using trend lines we can discover new patterns emerging from data points present in a graph or chart.

For instance, if we have a trend line over a sales chart, we can infer whether the sales are increasing with time,decreasing or not changing at all.

Also, trend lines help us in interpreting data trends, predicting future scenarios and draw a correlation between two variables in the analysis.

Q.49. How are Density maps different from normal maps?

The density maps specifically show a focus area of the whole data drawing the users attention at the points where data is concentrated or sparse because it helps in understanding data trends and patterns overall.

Whereas, a simple map in Tableau is used to graphically represent geographic data such as voters in every state of India, sales of product in different countries etc. 

Q.50. What is Branding in Tableau?

Tableau branding is nothing but customizing the appearance of a visualization in a Tableau way.

In an attempt to Tableau Branding, we can customize different aspects related to the appearance of a visualization such as font, color, size, shape, background, boundaries, transparency, highlighting etc. 

Q.51. What are Parameters in Tableau?

Parameters are containers for variable data values or those values that do not originally exist in the data source.

For instance, we can create a parameter field by setting a condition to it that it can take only of a certain type and a particular range.

Similarly, parameters gives us the flexibility to give any condition for the field like less than, greater than, top five, top ten etc.

A parameter can be a string value, a numeric value, a range of numbers, a currency etc. 

Q.52. Why do we use Lasso and other such tools in Tableau?

Tableau offers us different kinds of selection tools like,

• Lasso selection tool: In a lasso selection tool, we select data points by drawing a free shape over an area. This free shape usually resembles a lasso. 
• Radial selection tool: In radial selection method, there is a circle of a certain diameter (depending upon your area of selection) that is drawn over an area.
• Rectangular selection tool: When you use this tool, there is a rectangle drawn over the area that you select. The area will contain the data points that we wish to select. In all the selection methods, the selected area is shown in blue.

The selection tools are used to select a particular group of values so that we can focus our analysis just on that set of values.

All these three types of selection methods are based on the shape of the selection area i.e. circular in radial, free shape in lasso and a rectangle in rectangular selection tool. 

Q.53. Explain clustering in Tableau.

• Cluster analysis is also known as clustering in Tableau is the process of dividing a data set into segments or clusters having relevant data values.
• Clustering helps us in doing a comparative analysis of data in. In clustering, similar or closely related values are clustered together into different clusters.
• While the values that are not closely related fall into another cluster.
• Clustering is done using specific clustering algorithms where similar values are kept together as a part of the group.
• In Tableau, we can have a cluster of up to seven color shades or codes at a time.
• The clustering algorithm used in Tableau is known as K-means clustering.  This algorithm divides a data set into K clusters or segments based on their similarity metrics.
• After this, it calculates the mean (mean of all the values in one cluster) for each cluster which gives the Centroid (cluster center) of a cluster.
• Then by using the centroid value for each cluster present, the values are placed in such a way that the total sum of distances between the centroid and concerning members in a cluster is minimum or as small as possible.
• In this way, the K-means algorithm gives us closely packed clusters each made of closely related or similar values.
• For instance, if we have sales data for a product for different types of consumers or buyers.
• Now, we want to analyze the purchasing capacity of consumers. For this, we can create clusters where we can segregate consumers based on their purchasing capacities.
• With the help of such a cluster, we can come up with strategies to maximize sales depending upon the purchasing or spending capacities of each group. 

Q.54. How can we enhance the appearance of a Tableau workbook?

There are a number of ways through which we can improve the appearance of our work in Tableau and make it more attractive for the users. 

• By changing the looks of dates that we use in Tableau by formatting options. 
• By formatting and improving the look of Tooltip contents. 
• By changing the order of color expressed in charts.
• By exposing the header.
• By making parameterized axis labels. 
• By using continuous fast filters for range values. 
• By creating a custom date hierarchy.
• By formatting table calculation results.

Q.55. Give us some performance optimization techniques in Tableau.

In Tableau, we can employ a number of techniques which are essentially troubleshooting techniques that help in optimizing Tableau’s performance. 

We can optimize Tableau’s performance by practicing the methods given below. 

1. Work with Log Files: Having your server log records with you can help in detecting issues that affect the working of Tableau Server. 

2. Troubleshoot Data Sources: If we are having issues regarding data sources not being able to connect to a data source, unable to discover a data source, etc.

We need to take care of the permission settings for data source connections and of the data source connection page. 

3. Troubleshoot Subscriptions: If you are having issues with your membership subscriptions and getting messages regarding inability to render information from Tableau on mail.

Then you need to take care of certain things such as incident database shutdown, foundation process timeout, no membership symbol, invalid memberships, etc. 

4. Troubleshoot SAML: We can investigate issues related to SAML (Security Assertion Markup Language) by using the log files that store SAML related information. 

5. Troubleshooting Mutual SSL Authentication: In order to resolve SSL authentication issues, we need to contact the Tableau Server Administrator. 

6. Handle Extract Refresh Alerts: We need to take care of the extract refreshes if they are not happening properly.

If the automatic refresh of data extracts are not timely, then we need to address this issue at the Tableau Server.

Once this issue is resolved, Tableau’s performance is improved greatly. 

7. Troubleshoot Inconsistent Process Status: Tableau’s performance is affected if there are issues in showing process status consistently.

We need to troubleshoot this issue at the Tableau Server to ensure smooth working of the software. 

Q.56. What is a Word Cloud in Tableau

A Tableau Word Cloud is a visualization type which displays words in a cluster or cloud like manner.

The size of words will depend on the frequency of their occurrence in a given body of text. We arrange our word cloud in different shapes, sizes, manners like horizontal lines, columns etc. 

Q.57. How can we create a calculated field in Tableau?

Calculated fields are of great use in Tableau. Calculated fields are most commonly used in Tableau to create bins.

To create a calculated field we need to;

• Go to the Data pane and right-click on a dimension. 
• A drop-down menu will appear. 
• From there select Create and then select Calculated field. 
• A small window will appear from where we can set parameters to create a calculated field and name it. 

Q.58. How to automate reports in Tableau?

We can automate the rate of data refreshing in our reports in Tableau. When we upload a report on the server, we can set the time intervals when we want to update our report with the latest data. This is known as automation of a report where we do not need to update a report manually. 

Q.59. How can we embed data views on webpages? 

Tableau has a feature to embed data views created in Tableau on web pages, internet portals, web applications, wiki pages, blogs etc.

The embedded data views are originally uploaded to the Tableau Server and their data is automatically updated on the web at regular intervals.

In order to access or use Tableau data views or worksheets or workbooks or dashboards on the web, the user needs to have proper licensing and access permissions from Tableau Server.

Therefore, a user who wishes to embed a Tableau view into a web page must have an authentic Tableau account.

That user can give access to other web users to view the Tableau data view by using the Guest user option. If we enable Guest user, anyone who accesses the web page can access the Tableau data view. 

Q.60. What do you understand by aggregation and disaggregation of data in Tableau? 

Data values in Tableau are broadly treated in two ways; aggregation or disaggregation. In aggregation, data values (particularly measure values) are combined together or aggregated to give a summarized or higher level of data for analysis. For instance, if we have a measure field containing sales values for different cities. We can aggregate these values to create averages, sums, etc. Aggregated fields are very useful in analysis. 

On the other hand, when we disintegrate grouped or aggregated data into its basic form then it is called disaggregation of data values.

For instance, if in an analysis we need to see which age group has the most frequent buyers of a product, we need disaggregated values of data because it makes the data values distinct and discrete instead of clubbing them together. 

Summary

So, this was all in DataFlair’s Tableau interview questions and answers article.

In this, we have discussed 60 frequently asked interview questions, some basic and technical interview questions in Tableau and some other important topics of Tableau which will help you to brush up your basics and technical skills.