Tableau Interview Questions

Top 50+ Tableau Interview Questions for 2024

Searching out for the frequently asked Tableau interview questions that could help you ace the interview? You’re at the right place as here we’ve covered top Tableau interview questions and answers.

The sheer volume of data generated in the world till now and the exponential growth in the pace of creation of data create possibilities as well as challenges. Presently, the world generates more than 2.5 quintillion bytes of data. Furthermore, estimates have also suggested that almost every person would generate 1.7MB of data every second by the end of 2023.

So, enterprises want comprehensive data visualization tools to collect, organize, refine, and analyze the data for achieving exceptional business advantage. The demand for Tableau as a popular data visualization tool has created potential career opportunities.

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Top Tableau Interview Questions

The aspiring candidates search for the frequently asked Tableau interview questions that can help them strengthen their preparations for careers in Tableau. Here is an outline of the latest Tableau interview questions and answers that can provide you the right support for starting a career in data visualization.

Tableau Basics Interview Questions

Whether you are a beginner or experienced candidate, you may come across a number of basic questions in the Tableau interview. So, here are the simple and straight most common Tableau interview questions you should go through.

1. What is Tableau?

This is one of the top Tableau interview questions among mandatory addition all candidates can expect. Tableau is a software solution for business intelligence and allows any individual to connect with their respective data. It can help in the visualization and creation of interactive and shareable dashboards.

2. What is the difference between Tableau and Traditional Business Intelligence tools?

Candidates can expect this most common Tableau interview question for their preparations. Tableau is different from traditional business intelligence tools in terms of the lack of any dependencies. Tableau is comparatively faster than traditional BI tools based on a complex set of technologies. Most important of all, Tableau provides the advantage of predictive analysis over traditional business intelligence.

3. What are the notable additions in the Tableau Product Portfolio?

This is also one of the most common Tableau interview questions candidates should expect in a real interview. Here is an outline of the different Tableau products.

  • Desktop
  • Server
  • Online
  • Public
  • Reader

4. What do you know about .twb and .twbx extension?

The .twb extension indicates an XML document containing all selections and layout made in a Tableau workbook. The document does not contain any data. On the other hand, the .twbx extension indicates a zipped archive that contains.twb and external files such as background images and extracts.

5. What data types are supported in Tableau?

Candidates should also prepare for this frequently asked Tableau interview question. The common data types supported on Tableau include,

  • Boolean
  • Date
  • Date and Time
  • Text or String
  • Whole Number
  • Decimal Numbers
  • Geographical Value

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6. Define Measures and Dimensions in Tableau.

This is also one of the top Tableau interview questions to test the knowledge of candidates about Tableau fundamentals. Measures are basically the measurable quantity or numeric metrics of data, which could be subject to analysis with a dimension table. On the other hand, dimensions are descriptive values for attributes to indicate multiple dimensions of every attribute. In addition, dimensions also provide a comprehensive outline of the multiple characteristics of each attribute.

7. What are the notable features of Tableau?

The significant features of Tableau are a mandatory addition in almost any outline of the most common Tableau interview questions. The noteworthy features of Tableau as a business intelligence tool are as follows,

  • Data blending and real-time analysis capabilities
  • DAX analysis function
  • Data collaboration and data notifications
  • Mobile-ready and shareable dashboards
  • Support for a list of native data connectors
  • Creation of no-code data queries
  • Support for importing all sizes and ranges of data
  • Data highlighting and filtering

8. What are the benefits of Tableau?

Candidates are likely to encounter this most common Tableau interview question referring to direct advantages of Tableau. The prominent benefits of Tableau include,

  • Speed
  • Increasing market share and popularity
  • Ease of use without programming or technical knowledge
  • Ease of publishing and sharing
  • Beautiful and highly interactive dashboard
  • Direct connection

9. What is the Tableau Server?

Tableau Server is the most prominent addition in the Tableau products. It is a communication tool that helps in sharing visualization and data connection information to clients and end-users. It is a crucial requirement for the functionality of Tableau as it addresses the management and execution of various crucial processes. You can find the following components in Tableau Server,

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

10. What are the Filters in Tableau?

This is also one of the frequently asked Tableau interview questions that candidates can come across. Tableau filters provide a reliable mechanism for restricting certain content of data from entering a Tableau dashboard, view, or workbook. The various types of Tableau filters include extract filters, data source filers, table calculation filter, context filters, filters on dimensions, and filters on measures.

Tableau Scenario-based Interview Questions and Answers

Tableau is one of the top data visualization tools so you shouldn’t expect straight questions in your Tableau interview. You may get a number of scenario-based Tableau interview questions. So, check out the questions below to prepare yourself for your interview.

11. What is the importance of Context Filters?

Candidates should expect this entry among the latest Tableau interview questions for testing practical knowledge. Context filters are essential for applying context to specific data subject to analysis. With the application of a context, users can set a perspective that enables the visualization of graphs and charts.

Also Read: What is Data Visualization?

12. What are the specific Field Operations you can perform on Tableau?

This is also one of the Tableau practical interview questions that candidates should prepare for successfully qualifying the interview. Fields are one of the crucial aspects of data management and analysis in Tableau. Tableau supports the following operations on data fields.

  • Combination of two or more fields
  • Grouping multiple fields
  • Addition of new files to a worksheet
  • Searching for existing fields
  • Creation of a calculated field
  • Development of parameters from fields
  • Renaming and reordering fields
  • Creation of a set of two fields

13. Define Quick Sorting in Tableau.

It is important for candidates to prepare for this entry among practical Tableau interview questions. Tableau provides the functionality of Quick Sort for instantly sorting data through visualization by clicking on a sort button. One-click on the Quick Sort icon arranges the data in ascending order, two clicks enable the descending sorting, and three clicks enable an applied sort.

14. What is a Tableau Worksheet?

The Tableau worksheet is one of the basic components of working with Tableau. It is a single view sheet containing various visualizations. It contains different elements such as filters, Data and Analytics pane, shelves, Show Me menu, cards, and legends. In addition, users can also find a blank area on the Tableau worksheet for creating visualizations. You can use one or multiple Tableau worksheets for the creation of workbooks, stories, and dashboards.

15. What are the possible ways to connect to a data source in Tableau?

This is one of the most common Tableau interview questions that candidates can expect in an actual interview. It is possible to connect to a Tableau data source in two significant ways. One is through a live connection, and the other method involves the creation of an extract from a data source.

In the case of a live connection, users can connect directly to a data source through a connector. Therefore, live connections are similar to online connections. On the other hand, the creation of an extract involves taking data offline and storing it in Tableau memory.

16. What are Groups and Sets in Tableau?

Candidates should also prepare for these types of latest Tableau interview questions for testing practical knowledge of Tableau. Groups are the set of dimensions grouped together for the creation of a category. For example, analysis of scores for different matches can involve a group “Matches” containing all the matches for a specific player. Sets are basically the subset of data developed in accordance with a set of specific criteria or conditions. Sets can serve a helpful purpose in analysis after creation.

17. What are some of the formatting operations you can perform on Tableau?

This is also one of the practical Tableau interview questions that you would come across. The formatting options on charts and graphs in Tableau are one of the foremost reasons for its notable popularity. The formatting options on Tableau provide considerable flexibility for creating visualizations according to the user’s preference and requirements.

18. What is the hierarchy in Tableau?

In use cases involving work with large volumes of data, the possibilities of faults in the organization of data increase prominently. Tableau provides the facility of creating hierarchies to ensure proper organization of data. The interesting factor is that hierarchies are in-built into user data on Tableau, enabling easier management, organization, and tracking of data.

19. What do you mean by aggregation and disaggregation of data in Tableau?

Candidates should also prepare for such Tableau interview questions on real-time applications of Tableau. Aggregation of data on Tableau is the process of creating a summary of the data for obtaining a single numeric value. The example of the sum/average salary for each employee indicates the aggregation of data.

On the other hand, disaggregation of data in Tableau is the process of emphasizing on each transaction for analysis of all measures independently as well as dependently. The example of estimates of individual salary transactions for each employee indicates disaggregation of data.

Tableau is one of the top data visualization tools. Check out the list of top Data Visualization tools to know about the other options.

20. What are the important components of the Tableau Dashboard?

The Tableau dashboard is one of the prominent topics for the best Tableau interview questions. The dashboard contains five components as follows,

  • Web page embedded in the dashboard
  • Vertical layout container for adding objects
  • Horizontal layout container for adding objects
  • A small WordPad for formatting and editing text
  • Image Extract for uploading images to dashboard from the computer

Tableau Interview Questions for Experienced

If you have gained some significant years of experience in using Tableau for data visualization, then the interviewer may test your knowledge at different levels with some difficult questions. So, here we cover some of the frequently asked Tableu interview questions for experienced candidates.

21. What are the proven ways for improving the performance of Tableau?

This is one of the most common Tableau interview questions that you may come across in interviews for experienced Tableau-based roles. The notable ways for improving the performance of Tableau include the following,

  • Hiding unused field
  • Reduction of the scope of data for decreasing data volume
  • Focus on using integers or Booleans in calculations in place of strings
  • Using an Extract for faster operation of workbooks
  • Removal of unnecessary sheets and calculations
  • Reduction of filter usage and alternative approaches for achieving similar results
  • Utilizing context filters
  • Reduction in the number of marks on the view for avoiding information overload
  • Utilize indexing in tables and using same fields for filtering

22. What are the Charts you should avoid using on Tableau unless there’s a valid reason?

Candidates could come across such experience-based Tableau interview questions. Users should avoid using 3D charts, Donut charts, and pie charts on Tableau. 3D charts could skew the visual representation of numbers, thereby creating difficulties in comparison and analysis of data. Donut charts and pie charts cannot provide the level of accuracy as bar charts. The areas and angles in pie charts and arc lengths in donut charts create complexities for comparison of data.

23. How can you ensure optimization of the Dashboard Performance in Tableau?

This is also one of the important Tableau practical interview questions that candidates should prepare for. The recommended best practices for improving the performance of the Tableau dashboard are as follows,

  • Reducing the number of records and fields
  • Reducing the marks or data points in the view
  • Using include filter and continuous data filter
  • Reduction of the number of nested calculations
  • Cleaning up your workbooks
  • Removal of custom SQL
  • Reducing the number of filters
  • Using action filters and parameters

24. What are the critical challenges in working with massive volumes of data on Tableau?

The noticeable challenges in working with massive volumes of data on Tableau are as follows,

  • Data extraction
  • Data testing
  • Slow running of View
  • Data alignment issues

25. What is a Level of Detail (LOD) expression in Tableau?

Candidates could also find this entry among Tableau interview questions for experienced professionals. The Level of Detail (LOD) expression in Tableau helps in running complex queries that involve different dimensions at the data source level rather than bringing all the data to Tableau interface.

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26. What do you mean by Tableau Public?

Tableau Public is a free online platform that allows users to create and share visualizations with the rest of the world. Created by Tableau Software, it is designed for people who want to make their data visualizations publicly available.

27. How do you create a calculated field in Tableau?

Creating a calculated field in Tableau is a way to create new data that is based on existing data. This can be done by using mathematical formulas to manipulate the existing data.

28. List out the properties of Tableau combined sets?

There are several properties of Tableau combined sets that make them valuable for data analysis. First, they allow for the creation of custom fields that can be used to better understand the data. Second, they can be used to create better visualizations by allowing different fields to be compared side-by-side. Finally, they can be used to create interactive visualizations that allow users to explore the data in new ways.

29. What is all about data visualization?

Data visualization is all about taking data and representing it in a way that is easy for people to understand. This can be done in a variety of ways, but Tableau is one of the best platforms for doing so. Tableau allows users to create beautiful visualizations that can be shared with the rest of the world.

30. Mention the different Tableau files?

There are four different types of Tableau files:

  • Workbooks,
  • Worksheets,
  • Data Sources, and
  • Bookmarks

Workbooks are the files that contain the visualizations and worksheets are the sheets within the workbooks that contain the data. Data sources are the files that contain the data that is used to create the visualizations. Finally, bookmarks are files that contain saved views of the visualizations.

31. Write about the basic difference between published data sources and embedded data sources in Tableau

There are two types of data sources in Tableau: published and embedded. Published data sources are stored in Tableau Server or Tableau Online, while embedded data sources are stored locally in the workbook.

The main difference between published and embedded data sources is that published data sources are accessible to anyone with access to Tableau Server or Tableau Online, while embedded data sources are only accessible to the person who created the workbook.

Another difference is that when you publish a workbook that uses a published data source, the data source is also published. This means that anyone who has access to the workbook can also access the data source. However, when you publish a workbook that uses an embedded data source, the data source is not published.

32. Mention about Longitude and Latitude in tableau

Longitude and latitude play an important role in tableau. By incorporating them into your visualizations, you can create more accurate and informative maps. Here’s a quick guide on how to use longitude and latitude in tableau.

When creating a new visualization, select the ‘Longitude’ and ‘Latitude’ fields from the ‘Dimensions’ pane. This will plot your data points on a map. You can then use the ‘Map Options’ to customize your map. For example, you can change the map type, add or remove map labels, and so on. Once you’ve got your map looking the way you want, you can start exploring your data. Tableau’s mapping capabilities allow you to quickly identify patterns and trends in your data.

33. What is the key difference between traditional BI tools and Tableau?

The key difference between traditional BI tools and Tableau is the way they approach data. Traditional BI tools follow a more traditional, top-down approach where data is collected, processed, and then presented in a digestible format. Tableau, on the other hand, relies on a bottom-up approach where users are encouraged to explore data on their own to uncover insights.

This difference in approach leads to some key advantages for Tableau. First, Tableau is much more user-friendly and interactive than traditional BI tools. This makes it ideal for users who want to explore data on their own, without having to rely on IT or other analysts to run queries. Second, Tableau is much faster and more flexible than traditional BI tools. This makes it ideal for rapidly changing data sets or for users who want to experiment with different data visualizations.

Overall, Tableau is a more modern, user-friendly, and flexible tool than traditional BI tools. While it may not be suitable for every use case, it is definitely worth considering for any organization that wants to empower its users to explore data on their own.

34. Mention the characteristics that you distinguish data source in Tableau

There are many different types of data sources that you can use in Tableau, and each has its own set of characteristics. Here are some of the most important factors to consider when choosing a data source:

Location: Where is the data located? Is it on a local machine, or in the cloud?

Size: How much data do you need to work with? Tableau can handle large data sets, but performance may suffer if you’re working with too much data.

Format: What format is the data in? Tableau can work with many different types of data, but some formats are easier to work with than others.

Updates: How often does the data need to be updated? Tableau can connect to live data sources, or you can extract the data into a static file.

Security: Does the data need to be secure? Tableau can connect to data sources that require authentication.

35. Explain all about data terminologies in Tableau?

Data visualization is a critical part of data analysis, and Tableau is one of the most popular tools for creating visualizations. However, before you can create a visualization, you first need to understand the data you’re working with.

Here are some of the most important data terminologies in Tableau, so that you can better understand how to use the tool.

  1. Dimensions and Measures

When you’re working with data in Tableau, you’ll always have a combination of dimensions and measures. Dimensions are the characteristics of your data, such as the name of a product, while measures are the numerical values associated with those dimensions, such as the product’s price.

  1. Discrete and Continuous

Dimensions and measures can also be classified as either discrete or continuous. Discrete data can only take on a limited number of values, such as the names of products, while continuous data can take on any value, such as a product’s price.

  1. Pie Charts and Bar Charts

When you’re visualizing data in Tableau, you’ll often use pie charts and bar charts. Pie charts are best used to compare proportions, while bar charts are better for comparing values.

  1. Groups and Sets

You can also group data together in Tableau. This can be useful for creating custom views of your data. For example, you could group all the products in your data set by category.

  1. Filters

Filters are a great way to focus on a specific subset of your data. For example, you could use a filter to only display data for a certain time period.

36. What are Joins in Tableau?

Joins in Tableau are a way to combine data from two or more data sources into a single view. For example, you could use a join to combine data from a sales database and a customer database.

There are four types of joins in Tableau: 

Inner joins return only the data that exists in both data sources.

Left joins return all the data from the left data source, and only the data from the right data source that matches the data from the left.

Right joins return all the data from the right data source, and only the data from the left data source that matches the data from the right.

Full outer joins return all the data from both data sources, even if there is no match

37. Mention about three Tableau limitation

There are a few limitations to Tableau that are worth mentioning. Firstly, the software can be quite resource-intensive, so it may not be suitable for older computers or those with limited RAM. Secondly, Tableau doesn’t have built-in functionality for some complex statistical analysis, so you may need to supplement it with other software if you’re working with large or complex data sets. Finally, Tableau’s visualizations can be somewhat static and lack the interactivity of other data visualization tools.

38. How do you perform load testing in Tableau?

Load testing is a process of putting stress on a system or application to see how it performs under pressure. It is usually done to find out if a system can handle a high volume of traffic or transactions without breaking down.

There are a few different ways to do load testing in Tableau. One is to use Tableau’s built-in performance recorder. This records all the interactions you have with Tableau Server and then plays them back at a higher speed to simulate a high volume of traffic. Another way to do load testing is to use a tool like JMeter. JMeter can be used to generate a high volume of requests to a Tableau Server and then measure the response time.

Finally, you can also use a tool like LoadRunner. LoadRunner can simulate a high volume of traffic and transactions by using multiple virtual users. It can also measure the response time of the system under test.

39. Why do you use a hierarchical field in Tableau?

There are a few different reasons why you might want to use a hierarchical field in Tableau.

One reason is that it can help you to better organize your data. If you have a lot of data points, it can be helpful to put them into groups. This way, you can more easily see patterns and relationships. Another reason to use a hierarchical field is that it can help you to make calculations. For example, if you want to find the average sales for each region, you can use a hierarchical field to do this.

Finally, using a hierarchical field can also help you to create better visualizations. For example, if you want to create a tree map, it can be helpful to use a hierarchical field.

40. Explain about the term filter actions in Tableau?

Filter actions in Tableau allow you to interact with your data in a variety of ways. You can use them to highlight data, filter data, and even perform calculations on your data.

Filter actions can be used to highlight data in a variety of ways. For example, you can use a filter action to highlight all of the data points in a certain category. You can also use filter actions to filter your data. For example, you can use a filter action to only show data points that meet certain criteria.

Filter actions can also be used to perform calculations on your data. For example, you can use a filter action to calculate the average value of a certain field.

41. Explain about the Tableau Data Extract

A Tableau Data Extract is a compressed and optimized snapshot of data that can be used to improve the performance of Tableau Desktop. When you create an extract, Tableau Desktop writes data to a file in the .tde file format. Tableau Data Extracts are designed to provide better performance than live connections to data sources, and they can be refreshed on a schedule.

42. List out the primary differences between blending and joining in Tableau?

Tableau offers two ways to combine data sources: blending and joining. Both methods have their own advantages and disadvantages, so it’s important to understand the difference between them.

Blending is best used when you want to combine data sources that have a common dimension. For example, you could combine data from two different sales databases that use different date formats. The key advantage of blending is that it doesn’t require you to combine the data sources into a single file.

Joining is best used when you want to combine data sources that share a common key. For example, you could combine data from a customer database with data from a sales database. The key advantage of joining is that it preserves all of the data in both data sources.

43. What is the parameter in Tableau?

In Tableau, a parameter is a global placeholder for a value that you can change at any time. This can be helpful when you want to dynamically change the data that’s being displayed in your viz. For example, you could create a parameter that lets you select the date range for your data.

44. What do you mean by story in Tableau?

A story in Tableau is a way of presenting data in a way that tells a story or highlights a particular finding. Stories can be created using the various visualization tools in Tableau, such as charts, graphs, and maps.

There are many ways to create a story in Tableau, but one of the most effective is to use the “Story Points” feature. This allows you to add annotations and comments to your data visualizations, making it easy to share your findings with others.

Story points are a great way to add context to your data and make it easy for others to understand your findings. When used effectively, they can help you communicate your data in a way that is both informative and engaging.

45. What are Shelves in Tableau?

Shelves are the graphical areas in Tableau where you can place marks and data. There are four main shelves in Tableau:

  1. The Filters Shelf
  2. The Columns Shelf
  3. The Rows Shelf
  4. The Marks Shelf

The Filters Shelf is where you can place dimensions or measures that you want to use to filter your data. For example, you could place the State dimension on the Filters Shelf to only show data for a specific state.

The Columns Shelf is where you can place dimensions or measures that you want to visualization on the x-axis. For example, you could place the Sales measure on the Columns Shelf to visualize sales data over time.

The Rows Shelf is where you can place dimensions or measures that you want to visualization on the y-axis. For example, you could place the Profit measure on the Rows Shelf to visualize profit data over time.

The Marks Shelf is where you can place dimensions or measures that you want to use to create marks in your visualization. For example, you could place the Product dimension on the Marks Shelf to create a mark for each product.

46. Define Dual axis in Tableau.

Dual axis in Tableau refers to the ability to plot two different measures on the same axis. This can be useful when you want to compare two measures that have different units of measure, or when you want to add a second level of detail to your visualization.

To create a dual axis visualization in Tableau, simply drag a second measure onto the plot area. Tableau will automatically create two separate axes, one for each measure. You can then format each axis independently to create the visualization that you want.

Dual axis visualizations can be very useful for comparative analysis. For example, you could compare sales and profit margins on the same plot. Or you could compare the number of new customers and the number of repeat customers. By using two measures, you can get a more complete picture of your data.

47. Explain all about Tableau Product Suite

Tableau’s product suite is designed to help you see and understand data in new ways. With Tableau, you can connect to almost any data source, then visualize and create interactive dashboards to share with others.

Tableau Desktop is the flagship product, and is used to design and build visualizations on your desktop. Tableau Prep is a new tool for data preparation, and Tableau Server is a platform for sharing visualizations and dashboards.

Tableau Online is a cloud-based version of Tableau Server, and Tableau Public is a free platform for sharing public data visualizations.

Whether you’re a business analyst, data scientist, or just someone who wants to better understand their data, Tableau’s products can help you see and understand your data in new ways.

48. Mention the difference between the Tree map and Heat map in Tableau?

Tree map and heat map are two popular visualization methods in Tableau. Both are great for visualizing data sets with many dimensions.

The main difference between tree map and heat map is that tree map is better for data sets with a large number of items, while heat map is better for data sets with a minimum number of items.

Tree map:

Tree map is a great visualization method for data sets with a large number of items. It allows you to see the relationship between items and their hierarchy.

Heat map:

Heat map is a great visualization method for data sets with a small number of items. It allows you to see the relationship between items and their values.

49. Explain all about the measure filter in Tableau?

The Measure filter in Tableau is a great way to quickly filter your data by a specific measure. This can be useful when you want to focus on a particular metric, or when you want to exclude a measure from your analysis.

50. Explain about stacked bar charts in Tableau?

Stacked bar charts are a great way to visualize data in Tableau. They allow you to see the distribution of data across different categories, while also allowing you to see how different categories contribute to the total.

To create a stacked bar chart in Tableau, simply drag a measure onto the Shelf, and then drag a dimension onto the Columns shelf. Then, right-click on the dimension and choose “Stack mark”.

One great thing about stacked bar charts is that they automatically sort the data in descending order, so you can easily see which categories contribute the most to the total. If you want to see the data for each category side-by-side, you can simply double-click on the dimension in the Columns shelf and choose “Dual Axis”. This will create a separate axis for each category, making it easier to compare the data.

Are You Ready for Your Tableau Interview?

Now, you can clearly notice the level of difficulty and comprehension in Tableau interview questions. The best practice to ensure your success is to start your preparations for the job interview before looking for jobs. You can use the above-mentioned questions to create the foundation for your preparation. Candidates can also depend on user groups and other sources of advanced Tableau interview questions to improve their command over Tableau.

On the other hand, comprehensive training in Tableau concepts and hands-on experience could also improve your capabilities for clearing interviews. Most important of all, certifications on Tableau can establish your identity as a Tableau expert while widening your knowledge of Tableau. If you are going for a Tableau interview as a fresher, we’ll recommend you to have some basic knowledge with our Tableau Fundamentals training course.

Learn the fundamentals of Tableau and start your preparations right now by exploring different Tableau interview questions!

About Aditi Malhotra

Aditi Malhotra is the Content Marketing Manager at Whizlabs. Having a Master in Journalism and Mass Communication, she helps businesses stop playing around with Content Marketing and start seeing tangible ROI. A writer by day and a reader by night, she is a fine blend of both reality and fantasy. Apart from her professional commitments, she is also endearing to publish a book authored by her very soon.

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