Top 60 Tableau Interview Questions and Answers for 2020
It’s time to turn your dreams of becoming a Tableau developer into reality by practicing these Tableau interview questions with their answers. These Tableau interview questions are curated by our experts which will help you to stand out in your interview and to get the best jobs as a Tableau Developer, Tableau Solution Architect, Tableau Analyst, etc.
In this article, we will be discussing the important Tableau interview questions and answers to brush up your skills. We have divided this article in the following categories:
- Basic Tableau Interview Questions and Answers
- Tableau Real-Time Interview Questions and Answers
- Top Tableau Interview Questions and Answers
- Tableau Developer Interview Questions and Answers
- Tableau Interview Questions for Experienced Professionals
Let’s start with some basic Tableau interview questions with their answers.
Basic Tableau Interview Questions and Answers
Q.1. What is Tableau?
Tableau is a data analytics and business intelligence platform which is flexible and easy to use ensuring a smooth experience to the users. The main pillars of strength for Tableau are interactive dashboards, quick responsiveness, and real-time data analysis. Also, it offers a wide range of eye-catching graphics or visualizations to represent your data set pictorially like charts and graphs.
Basically, Tableau provides all the capabilities that we require for a successful data analysis like data extraction, processing, representing/visualizing and sharing the final reports/dashboards/worksheets with others.
Q.2. What are the advantages of using Tableau?
Tableau is a BI tool that is designed to help the user to create visuals and graphics. One can do this without any technical help or prior knowledge of programming. There are a lot of advantages of Tableau such as:
- Speed
- Ease of use
- Beautiful and interactive dashboard
- Direct connection
- Easy publishing and sharing
- Growing market share and popularity
Explore the pros and cons of Tableau for a better understanding of Tableau.
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
Get a detailed insight of Tableau features with Omni Academy
Q.4. 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.
Tableau Real-Time Interview Questions and Answers
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.
Learn to create Dashboards in Tableau.
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 files contains information about worksheets and dashboards that are present within a Tableau workbook. That is, all the information related to fields, aggregation types, styles, formatting, filters, etc are present in these files.
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.
Time to know how to change Data Types in Tableau.
Top Tableau Interview Questions and Answers
Q.12. What are measures and dimensions in Tableau?
Measures: 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: 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.
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?
Data extracts are portions of data that we take from the data source. 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.
Know how to extract data in Tableau with Tableau Data Extracts.
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.
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.
Tableau Developer Interview Questions and Answers
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 Tableau maps. 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.
Get the best out of your data using Tableau Filters.
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.
Tableau Interview Questions for Experienced Professionals
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.
Have complete knowledge of Tableau Data Sources with DataFlair.
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?
Shelves: 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.
Summary
So, this was all in DataFlair’s Tableau interview questions and answers article. In this, we have discussed the 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.
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If you have any doubts related to these Tableau interview questions or any other questions related to your previous interview ask in the comment section. We will be happy to help you.
Happy Learning😃
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