67 Frequently Asked Tableau Interview Questions and Answers

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Tableau is one of the most popular business intelligence and data visualization tools used by organizations of all sizes. As Tableau usage grows, demand for Tableau experts is also increasing. In this comprehensive guide, we have curated a list of 67 frequently asked Tableau interview questions to help you prepare for your next Tableau job interview.

Tableau Basics

1. What is Tableau and how is it useful for businesses?

Tableau is a data visualization tool that helps businesses visually analyze their data to find insights, patterns and trends. It connects to almost any kind of data source and allows users to create interactive dashboards and reports without writing any code. This enables faster and smarter data-driven decision making.

2. What are some key features of Tableau?

Some key features of Tableau include:

• Interactive and dynamic drag-and-drop dashboards
• Support for live data connections
• Powerful in-memory data engine for fast performance
• Wide range of visualizations (charts, graphs, maps etc.)
• Ad-hoc reporting and analysis
• Data blending from multiple sources
• Mobile reporting across devices
• Robust security and governance

3. What are the different Tableau product offerings?

The main Tableau product offerings are:

• Tableau Desktop: Primary end-user analytics and visualization desktop tool
• Tableau Prep: Data preparation tool for combining, shaping and cleaning data
• Tableau Server: Enterprise platform for sharing analytics, dashboards and reports
• Tableau Online: Cloud version of Tableau hosted by Tableau
• Tableau Reader: Free desktop application for viewing and interacting with Tableau dashboards

4. What are the different types of data sources supported by Tableau?

Tableau can connect to almost any kind of data source across organizations. Some of the commonly used data sources are:

• Relational databases: MySQL, SQL Server, PostgreSQL etc.
• Cloud-based: Google BigQuery, Amazon Redshift, Snowflake etc.
• Files & Excel: CSV, TXT, JSON, XLSX etc.
• Big Data: Hadoop Hive, Spark SQL
• Applications: Salesforce, Google Analytics, Marketo etc.

5. What are Tableau Data Extracts and their benefits?

Tableau Data Extracts are portable, offline copies of data from different sources aggregated into a single .tde file. Some benefits of using extracts are:

• Improved performance for large datasets
• Ability to work without live data connection
• Apply additional data shaping and preparation
• More features supported compared to live data
• Secure data sharing since extracts contain only required data

Using Tableau

6. How do you connect to data in Tableau?

Connecting to data is very easy in Tableau. You can simply click on any of the supported data sources in the connect pane. Tableau will automatically detect the data types and display a preview of data. You can then import the data by dragging tables or selecting sheets.

7. Explain the difference between dimensions and measures in Tableau.

Dimensions are categorical attributes that break down the numerical attributes. For example – region, product names, market etc.

Measures are the quantitative or numerical attributes that can be measured and analyzed. For example – profit, revenue, sales etc.

8. How do you filter data in Tableau?

There are multiple ways of filtering data in Tableau:

• Using filter tray: Drag a field to Filters shelf and select filter values
• Filter controls within views
• Context filters: Right click on a value and ‘filter out‘ the selection
• Filter actions: Interactive filtering via actions between dashboards
• Extract and data source filters: Apply while importing data

9. How do you group data in Tableau?

To group data fields in Tableau:

• Drag a dimension with discrete values to Rows or Columns shelf
• Select the members you want to group either from view or from Data pane
• Right click and select ‘Group‘ option
• A new group field will be created with given set of values

10. How do you aggregate data in Tableau?

We can aggregate data in Tableau using:

• Aggregate Functions: In-built functions like SUM(), MIN(), MAX(), AVG() etc.
• Quick Table Calculations: Options for table calculations like year over year growth, moving average etc.
• Custom Aggregations: Build custom aggregation logic using Level of Detail expressions

Tableau Desktop

11. What are the main components of Tableau Desktop UI?

The key components of Tableau Desktop UI are:

• Data pane: Lists available data sources, metadata and profile information
• Analytics pane: Drag-and-drop shelves for analysis – Columns, Rows, Pages, Filters, Measures
• Dashboard pane: Contains tabs for added sheets, dashboards and stories
• Marks card: Provides options for quickly changing chart type and formatting

12. What chart types does Tableau support?

Tableau supports a wide variety chart and graph types for data visualization such as:

• Bar charts, Line charts, Pie charts, Tree maps and Scatter plots
• Heat maps, Box and whisker plots, Histogram, Waterfall
• Map charts, Area charts, Dual axis charts
• Gantt charts, Bullet graphs and more

13. What are Parameters in Tableau? How are they useful?

Parameters are dynamic dashboard variables that can be used for interactive filtering, actions and calculations.

Parameters make dashboards more flexible, allowing user input to control the data and view. It eliminates the need to create multiple similar reports for different values.

14. How can you optimize data extracts and data sources for performance?

Some ways to optimize Tableau for performance:

For extracts – Take only required tables and fields; Apply filters, aggregations etc. during extract creation; Build indexes on important attributes

For data sources – Reduce number of live data connections; Create extracts; Leverage data server caches and materialized views

Also optimize queries, calculations, visualizations and dashboards to minimize load on data sources.

15. What are Tableau Actions and how do you use them?

Tableau actions allow linking between dashboards and sheets to enable interactive analysis by filtering across various views.

To create cross-sheet actions, associate the source sheet selection with target sheets via menu. Use ‘Add Action‘ and define action type. The action gets triggered when selecting marks in the source sheet.

Tableau Server

16. What is Tableau Server? What features does it provide?

Tableau Server is an enterprise platform to centrally host, manage and share analytics assets in a secure and scalable manner. Key features include:

• Centralized portal for publishing dashboards
• User access control and permissions
• Usage monitoring and tracking
• Scalability through clustering
• Automated subscriptions and alerts
• Data refresh scheduling and monitoring
• API and metadata integrations
• Mobile Analytics

17. How does data refresh work in Tableau Server?

Tableau admins can set up refresh schedules for published data sources and extracts. During data refresh, Tableau Server pulls the latest data, reloads it incrementally and updates dashboards.

Configurable scheduling options include ability to set frequency, customize times, add dependencies between sources and specify refreshing priority between extracts.

18. What are the different Tableau Server roles?

The Tableau Server roles are:

• Server Administrator: Manages all aspects of server
• Site Administrator: Manages sites and content
• Creator: Creates, edits and publishes content
• Explorer: Views and interacts with published content
• Unlicensed: View only access but cannot interact

Besides the standard roles, custom roles can be created by assigning granular functional permissions.

19. How can you optimize performance of Tableau Server?

Some ways of optimizing Tableau Server performance are:

• Choose performant hardware with sufficient capacity
• Limit number of live connections; Schedule frequent extract refreshes
• Use Initial SQL option for fast visualization rendering
• Reduce size and complexity of data sources
• Simplify dashboard design; Apply filters before larger transformations
• Investigate performance profile using Server Manager
• Scale out to handle high loads by adding nodes

20. What options do you have for scaling out Tableau Server deployments?

Tableau Server enables scaling out analytics delivery to support a large number of users. Some scale-out options are:

• Add more nodes to Distributed/Clustered installations
• Allocate dedicated backgrounder nodes
• Enable and configure Hyper software for faster queries
• Deploy server on public cloud for elastic capacity
• Geographic distribution across zones for proximity
• Server caching for hot dashboards
• Load balancing (via proxy) for high availability

21. What authentication mechanisms does Tableau Server support?

Tableau Server supports:

• Local authentication – Users and groups managed internally
• Trusted authentication – Via SAML, Kerberos and OAuth
• Delegated authentication – Using external Identity stores

This enables both local and enterprise-wide authentication via single sign-on across systems.

Advanced Tableau Concepts

22. How can you establish live connections between Tableau and R or Python?

Tableau can connect to both R and Python using tabPy technology. Python scripts and R models can be accessed via Tableau calculated fields.

To enable:

1. Start Python or R server process (tabPy or RServe)
2. Configure server details in Tableau
3. Call scripts functions using SCRIPT_*() syntax

23. What is Tableau Data Blending? When would you use it?

Tableau data blending enables combining data from multiple sources into a unified view without the need to permanently join them together.

You would use data blending when:

• Dealing with very large data sources
• Combining data inputs with different refresh rates
• Mashup of different data types like relational + cloud
• Need flexibility to update sources independently

24. How to establish live connection between Tableau and Mapbox?

To connect Tableau and Mapbox – a popular interactive mapping platform:

1. Get Mapbox account and access token
2. From Tableau Desktop, select ‘Web Data Connector‘ as data source
3. Enter URL: https://mpb.mapbox.com?access_token={token}
4. Configure required geospatial data sources
5. Visualize data over Mapbox base maps

25. What is visual customization in Tableau 10.5?

Tableau 10.5 adds support for visual embedding via extensions API and deep integration with R and Python.

Custom visualizations created using D3 can be packaged as Tableau extensions and imported into Tableau. This allows leveraging JavaScript libraries, R ggplot2 and Matplotlib Python charting capabilities.

26. In Tableau Server notification system, how do subscriptions differ from alerts?

Tableau subscriptions automatically deliver specified reports and dashboards to users via emails at scheduled intervals. They allow containers and attachments.

Whereas alerts continuously monitor dashboard data and trigger email if conditions match. Alerts require less configuration but only allow single sheet attach.

27. What is TabPy and how does it enable scaling in Tableau?

TabPy is a Python service that allows Tableau to offload heavy computations to an external Python process. It acts as client to TabPy server for accessing Python analytics at scale.

This helps Tableau leverage Python for advanced analytics while overcoming Tableau processing limitations as computations run on TabPy server outside Tableau.

28. Can you publish Tableau dashboards to Power BI and Salesforce?

Yes, Tableau provides native options to embed or publish Tableau dashboards into other platforms using iFrames.

For Power BI, Tableau contents can be embedded as native Power BI visual.

For Salesforce, Tableau dashboards can be integrated using embedded link or Salesforce Lightning web component.

Tableau Administration

29. How do you license Tableau Server?

Tableau Server requires purchased device-based licenses for authoring and viewing capabilities. Following license types are available:

• Creator: Provides edit/publish capabilities
• Explorer: Read-only viewing license
• Viewer: Restricted functionality viewing

Licensed user accounts can sign-in and access Tableau Server as per permissions.

30. As a Tableau Server admin, how do you monitor health status?

Tableau Server Manager provides monitoring interface to track Tableau health stats covering:

Processes: Server Agent, Cache Server, VizQL processes

Background Tasks: Extract refreshes, subscription events

Resource Usage: CPU, load, disk space, memory, sessions

Performance: Request queue size, active sessions, load times

Alert rules can also be set up for email notifications on issues.

31. What are Tableau Data Server and Tableau Data Management?

Tableau Data Server provides managed and certified data engine option combining enterprise databases like Teradata with Tableau’s VizQL analytics engine for governed data access.

Tableau Data Management adds self-service data preparation and catalog with governance across multiple data sources like Hadoop, relational databases etc. It provides a business semantic layer over IT data infrastructure.

32. What backup and recovery options does Tableau Server provide?

Tableau Server enables the following data protection capabilities:

High Availability (HA): Clustering, Failover avoidance during node failures

Incremental Backup: Utility to backup metadata incrementally

Full Backup and Restore: Automated snapshots of critical databases and configs

Disaster Recovery: Offsite backups to recover server installation after disaster

These capabilities can be customized as per needs and infrastructure.

33. Can you implement row-level security in Tableau?

Yes, Tableau supports row-level security i.e. access control per user or groups for rows in a database table by filtering data based on user context.

It integrates with popular data platforms like Teradata, Cloudera Impala, Databricks and leverages their native row-level security functionality.

34. In Tableau Catalog, what are Saved Data Sources and Shared Data Assets?

Saved Data Sources in Catalog contain pre-configured connections to databases and files along with any data prep workflows applied to them. Users can discover these certified sources and leverage them.

Shared Data Assets are reusable definitions like metrics, calculated fields, groups and bins that are made available to users for consumption across the organization via self-service paradigm.

Troubleshooting in Tableau

35. You are seeing performance slowdowns in dashboard. What techniques can you use to troubleshoot?

Some techniques for troubleshooting Tableau performance:

• Examine dashboard performance recording for spike analysis
• Drill down step-by-step to isolate pain areas
• Simplify complex calculations, visualizations
• Remove action filters, cross-sheet interactions
• Use exclude Filters instead of context filters
• Compare load times across recent versions
• Break into clusters to minimize resource load

36. What are some common errors in Tableau Desktop?

Some frequently encountered Tableau Desktop errors are:

• Unexpected database disconnections
• Data source refresh failures, timeout errors
• Permission issues accessing files/data
• Extract creation or refresh issues
• Insufficient disk space error
• Workbooks failing to open/save
• Tableau crashing intermittently

37. How can you troubleshoot ‘Insufficient Memory‘ errors during Extract refresh?

In case of memory errors while extracting data in Tableau Desktop:

• Close other applications to maximize available system memory
• Increase extract creation memory allocation limit under preferences
• Extract less data by removing unnecessary fields or apply filters
• Use full, faster system drive with ample space

If issue persists on high-spec machine, explore sampling or optimize performance.

Tableau Interview Questions – Conclusion

38. How is Tableau different compared to traditional business intelligence platforms?

Instead of just enabling analysis and reporting like traditional BI, Tableau completely transforms understanding of data through interactive, self-service visual analytics. Its intuitive drag and drop interface makes visualization seamless without needing SQL or programming expertise.

Tableau’s associative analytics enhances creativity and speed in spotting insights as users get immediate feedback to questions simply by pointing and clicking. The shifts users from waiting for reports to exploring data freely and iteratively.

39. What makes Tableau a great data visualization and BI tool choice?

Tableau leads the industry as an enterprise-ready interactive data visualization tool enabling faster and smarter business decisions via easier access to insights from data.

Specific capabilities like speed, scalability, flexibility, advanced analytics integration and strong collaboration features make Tableau a great BI tool. It can handle massive data volumes while delivering outstanding query performance and rich analytics.

40. Why is Tableau knowledge important from a career perspective?

Tableau has been a top skill for business analysis and data science roles over the years. Being Tableau certified can be a great learning for anyone from students to experienced professionals.

As world’s leading analytics platform deployed widely across companies and industries, having Tableau expertise helps boost both technical and business skills. With surging job demand and salaries for Tableau experts, it provides fantastic career benefits.

I hope these Tableau interview questions have been helpful. If you have any other Tableau questions, please ask in the comments!