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Tableau Interview Questions and Answers

Last Updated : 24 Feb, 2024
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Tableau is a powerful data visualization tool that turns raw data into understandable insights. It helps users create interactive and shareable dashboards, charts, and reports, making it easier to analyze and communicate complex data trends for better decision-making in business and other fields.

In this article, we have provided you with the top 50+ Tableau Interview questions with answers that cover everything from basics to advanced. Whether you are a fresher or an experienced IT professional (5 years or 10 years of experience ), this article gives you all the confidence you need to ace your next Tableau interview in one go!

Tableau Interview Questions

Tableau Interview Questions for Beginners

1. What is Tableau?

Tableau is a powerful visualization and business intelligence software application that enables users and other organizations to create shareable, interactive dashboards, reports, and data visualizations. It is widely used for data analysis and reporting purposes.

2. What is a tableau reporting tool?

Tableau is a potent business intelligence (BI) and data visualization software program used to create interactive and shareable reports and dashboards. Users can connect to different data sources with it, transform unprocessed data into insightful visuals, and derive insights from their data. The user-friendly design of Tableau and its wealth of tools for data exploration, analysis, and storytelling are well-known.

To transform data into usable insights, make data-driven choices, and effectively convey findings through interactive reports and dashboards, it is widely utilized in businesses across industries. The several editions of Tableau include Tableau Desktop (for authoring reports), Tableau Server (for sharing and collaborating on reports), and Tableau Online (a cloud-based version).

3. What do you understand by Business Intelligence?

Business Intelligence is a method that utilizes technology for data analysis and information delivery that aids leaders, managers, and employees in making strategic business decisions. As part of the BI process, organizations gather data from internal IT systems and external sources, prepare it for analysis, run queries against the data, create data visualizations, BI dashboards, and reports, and then make the analytics results accessible to business individuals for decision-making related to operations and strategic planning.

4. What is the difference between Power BI and Tableau?



Power BI

Provider Tableau is an independent company that was later acquired by Salesforce. It operates independently but also has integrations with Salesforce products. It is developed by Microsoft, Which is a component of the Microsoft business that easily interfaces with Microsoft products including SQL Server, Azure, and Excel.
Ease of Use Although Tableau has a more difficult learning curve than Power BI, it offers more sophisticated customizations and analytical features. It is preferred by data analysts and experts. Power BI, which is well known for its user-friendly interface, is frequently appreciated for its simplicity of use, which makes it available to a wider range of customers.
Data Connectivity Tableau provides a wide range of data connectors and integration tools, making it suited for integrating with a variety of data sources, including databases, online services, and cloud platforms. It provides a large choice of native connectors for connecting to different data sources, like as Excel, SQL servers, and cloud-based applications. Also, it supports unique data connectors.
Visualization Tableau, which excels in complicated visuals, offers a wide range of customization options. Users who need extensive data exploration and visualization tend to favor it. It provides customers with a wide range of visualization options and allows for the easy creation of interactive reports and dashboards. With regard to advanced analytics, it might have some restrictions.
Collaboration It allows for sharing and collaboration via the Tableau server and Tableau online. It offers fine-grained control over user access and permissions. Power BI Service enables collaboration and the sharing of reports and dashboards with coworkers and clients. It allows simple connectivity with Teams and Sharepoint.

5. What are the different Tableau Products?

Different products of Tableau are :

  • Tableau Desktop
  • Tableau Server
  • Tableau Online
  • Tableau Public
  • Tableau Prep
  • Tableau Mobile
  • Tableau Reader
  • Tableau Prep Builder

6. What are the different datatypes in Tableau?

Tableau supports 7 various different data types:

  • String
  • Numerical values
  • Date and time values
  • Boolean values
  • Geographic values
  • Date values
  • Cluster Values

7. What is the difference between Measures and Dimensions in Tableau?

Attributes Dimension Measure
Nature They are categorical or qualitative data fields. They represent categories, labels, or attributes by which you can segment and group your data. They are numerical or quantitative data fields. They represent quantities, amounts, or values that can be aggregated, or calculated.
Usage They are used for grouping and segmenting data, creating hierarchies, and the structure for visualizations. They are used for performing calculations and creating the numerical representation of the data as sum, average, etc.
Example Category, Region, Product name, etc. Sales(sum of sales), Profit(sum of profit), Quantity(sum of quantity), etc.

8. What are the different file extensions used in Tableau and what are their significance?

Tableau uses several file extensions for different purposes within its ecosystem. Here are the most common file extensions used in Tableau and their significance:

  • .twb (workbook): It represents a Tableau workbook, focusing on the layout and visualization details created in the Tableau desktop. It only contains the references to the location of the data source rather than the actual data itself. .twb files are smaller in size due to their lightweight nature. Receivers of .twb files must have access to the associated data source in order for the workbook to operate properly.
  • .twbx (Packaged workbook): It is known as Tableau packaged workbooks and provides a comprehensive solution for sharing Tableau workbooks. They include both the actual data source and the workbook layout, including any custom calculations and visualizations. This embedded data ensures that recipients can open and view the workbook independently of the original data source. However, .twbx files tend to be larger due to the included data.
  • .hyper (Data Extract File): To enhance the performance of the data in Tableau Workbooks, a Tableau Data Extract File (.hyper) is employed. For quicker querying and analysis, it maintains a snapshot of the data from the data source. When you import or export data from external sources, you may produce hyperfiles.
  • .tds(tableau data source): It saves data source connections and schema information without data, facilitating consistent data source usage across multiple workbooks.
  • .tdsx(packaged data source): It is a packaged version of a data source that includes a data source and associated extracts, ensuring comprehensive sharing.
  • .tbm(Tableau Bookmark): It saves a snapshot of a single visualization within a workbook, allowing users to share specific insights or views.
  • .twbx(Tableau Server Workbook): Optimized for server deployment, it is used for publishing Tableau workbooks to the Tableau server or Tableau online for web-based access.
  • .tds(Tableau server Data source): Published data source files on Tableau serve or Tableau online for collaborative data analysis among users on the server.

9. What data sources can you connect to the Tableau?

With the help of Tableau, a potent business intelligence and data visualization tool, you can build engaging visualizations of a variety of data sources. Numerous data sources are supported by Tableau, such as:

  • Databases:
    Relational databases like MySQL, PostgreSQL, etc., NoSQL databases like MongoDB, etc., and Cloud-based databases such as Amazon Redshift, snowflake, etc.
  • Cloud Storage Services:
    Amazon S3, Google Cloud Storage, and Azure Blob Storage
  • Web Connectors:
    It provides different web connectors to connect to web-based APIs and services, allowing you to pull data from sources like Google Analytics, Salesforce, JSON, etc.
  • Statistical and Analytics software:
    Integration with statistical tools like R and Python to execute advanced analytics and machine learning models.
  • Data Servers and OLAP cubes:
    Connection to data servers and OLAP cubes, such as Microsoft Analytics Services(SSAS) and SAP HANA.
  • Excel and Text files:
    You can directly connect to Microsoft Excel spreadsheets and text files(CSV, TSV) to import data.

10. What kinds of connections can you build with your dataset in Tableau?

In Tableau you can create different types of connections with your dataset:

  • Live Connection: Real-time link to the data source for instant updates.
  • Extract Connection(TDE): Snapshots of data for improved performance and scheduled refreshes.
  • Blended Data Connection: Combine data from multiple sources in one visualization.
  • Data source Union: Combine related tables or sheets within the same source.
  • Cross-Database Join: Join tables from different databases or sources.
  • Custom SQL Connection: Write custom SQL queries for data retrieval.
  • Web Data Connector: Fetch data from web-based APIs.
  • Local File Connection: Connect to local files(eg., Excel, CSV)
  • Cloud Data Connection: Link to data in cloud-based services(e.g, AWS, GCS)

Intermediate Tableau Interview Questions

11. What are the different types of joins available in Tableau?

There are different types of joins in Tableau:

  • Inner Join: An inner join returns only the rows that have matching values in both tables. Rows that do not have a match in the other table are excluded from the result.
  • Left Join: A left join returns all the rows from the left table and matching rows present in the right table. If there is no match in the right table, null values are included in the result.
  • Right Join: A right join returns all the rows from the right table and matching rows present in the left table. If there is no match in the left table, null values are included.
  • Full Outer Join: A full outer join returns all the rows where there is a match in either the left or right table. It includes all the rows from both tables and fills in null values where there is no match.

12. What’s the difference between joining and blending?

Basis Joining Blending
Data Source Requirement Joining is basically used when you have data from the same data source, such as a relational database, where tables are already related through primary and foreign keys. Blending is used when we have data from different data sources. such as a combination of Excel spreadsheets, CSV files, and databases. These sources may not have predefined relationships.
Relationships The foundation for joins is the use of common data like a customer ID or product code to establish predetermined links between tables. These relations are developed within the same data source. There is no need for pre-established links between tables while blending. Instead, you link different data sources separately and combine them by matching fields with comparable values.
Data Combining When tables are joined, a single unified data source with a merged schema is produced. A single table with every relevant field is created by combining the two tables. Data blending maintains the separation of the data sources. At query time, Tableau gathers and combines data from several sources to produce a momentary, in-memory blend for visualization needs.
Data Transformation It is useful for data transformation, aggregations, and calculations on the combined data. The information from many connected tables can be used to build computed fields. It is only useful for data transformation and calculations. It cannot create calculated fields that involve data from different blended data sources.
Performance Joins are more effective and quicker than blending because they leverage the database’s processing power to perform the merge It can be slower than joining because it involves querying and combining the data from the different sources at runtime. Large datasets in particular may have an impact on performance.

13. How to view SQL generated by Tableau Desktop?

In Tableau Desktop, you can view the SQL generated by your data source by following these steps:

  • Open the workbook where you have connected to your data source and go to the “Data” menu.
  • Click on the “Data Source” tab within the “Data menu”.
  • In the “Data Source,” you will see the “Analysis” tab, in which you can find the “Custom SQL” pane.
  • Click on the “Custom SQL” pane to view SQL queries generated by Tableau for your data source.

14. How do you create a dashboard in Tableau?

Creating a dashboard in Tableau allows you to combine multiple visualizations, sheets, and objects into a single interactive canvas for data presentations and explorations. Here is a step-by-step guide on how to create a dashboard in Tableau:

  • Open the workbook that contains worksheets you want to include in your dashboard. Ensure that you have already created worksheets that contain the visualizations and data you want to display.
  • Click on the “Dashboard” tab at the bottom of the screen. In the dashboard workspace, you’ll see a blank canvas.
  • Drag and drop objects, from the left sidebar onto the dashboard canvas. Objects can include sheets, images, web content, text, and more.

15. What is the difference between the Tableau Worksheet, Dashboard, Story, and Workbook?

  • Dashboard: A dashboard is a group of views (worksheets) grouped on one page to offer an interactive and comprehensive view of data. They consist of graphs, maps, tables, and other online material. Dashboards enable consumers to fully show and comprehend data by combining many visuals into a single interface. They work on creating interactive reports and giving out instant insights. 
    Dashboards provide actions and interaction, allowing users to dynamically filter and emphasize the data. With the use of simple filters and parameters, dashboard behaviour can be changed.
  • Worksheet: To develop a data visualization, a worksheet is used as the basic building block. Drag and drop fields onto the sheet or canvas to construct tables, graphs, and charts. We may develop several types of charts, add filters, and change the formatting inside a worksheet. They are used to design unique visualizations.
    Various visualization choices, including as bar charts, line charts, scatter plots, etc., are available in worksheets. Reference lines, data blending, and the creation of computed fields are also possible.
  • Story: When sheets are combined to produce a logical flow, a story is created as a sequence or narrative. Each plot point corresponds to a particular stage of the story. Stories are employed to guide viewers step-by-step through a collection of visualizations or insights. For telling data-driven stories or presenting data-driven narratives, they are helpful. 
    Each story point can have text comments, captions, and descriptions added. Interactive narrative navigation is available to readers.
  • Workbook: The highest-level container in Tableau is this one. It is a document that can accommodate numerous spreadsheets, dashboards, and tales. Workbooks house the entire Tableau project, including data connections and visualizations. They are the main files used to create, save, and share projects in Tableau. All the elements needed for data analysis and visualization are kept there.
    Workbooks can be used to arrange numerous worksheets, dashboards, and narratives. You can establish data source connections, provide parameters, and create calculated fields at the workbook level.

16. What is the difference between a discrete and a continuous value in the Tableau?

  • Discrete Fields: They are made to handle qualitative or categorical data, such as names, categories, or labels. With no intrinsic order or measure attached to these values, each value within a discrete field indicates a unique category or group. The addition of discrete fields to a Tableau view is indicated by the presence of blue pill-shaped headers, which are often positioned on the row or column shelves. They successfully create headers for each split and separate the data into distinct groups.
  • Continuous Fields: They are made to handle numerical or quantitative data, which includes measurements, values, or quantities. Because continuous fields naturally have an order, mathematical operations like summation and averaging are feasible. These fields are identified in Tableau views by green pill-shaped heads that are frequently found on the rows or columns shelf. When present in a view, continuous fields show a continuous range of values for the selected measure or dimension.

17. What are groups, sets, and parameters in Tableau?

  • Sets: Sets are utilized to create unique data subsets based on predetermined criteria or standards. You can dynamically segment your data with their help, which makes it easier to analyze and visualize various subsets. Sets are constructed from measurements or dimensions and might be categorical or numerical. You can highlight specific data points, compare subsets, or make calculations in real time with these adaptable tools. For instance, you could build a group of “Hot Leads” from prospective clients with high engagement scores, or you could choose clients whose cumulative spending exceeds a certain threshold to create a group of high-value clients. Because they can alter as the data does, sets are flexible and dynamic for a range of analytical tasks.
  • Groups: To integrate persons (dimension values) into higher-level groupings, groups are used. They accomplish this by dividing similar numbers into helpful groups, which clarifies complex data. Groups are static, therefore the members of the group are constant and do not change as a result of the data. The classification and labelling of data points depend heavily on groups, which are often built from dimensions. You may, for instance, combine smaller product subcategories into larger categories or create your own dimension by fusing other dimensions. Groups can be used to structure data presentation and organization, making it simpler to analyze and visualize.
  • Parameter: A parameter is a dynamic control that lets a user enter a single value or pick from a predetermined list of values. By enabling users to change a range of visualization-related components without having to engage in extensive editing or alter the data source, parameters in Tableau dashboards and reports promote interactivity and flexibility.

18. What is the difference between sets and groups in Tableau?





A set is a specially created subset of data based on particular requirements or criteria. Sets can be either dynamically changing or static, allowing for the development of a binary split where objects either belong to the set or do not.

A group combines several members of a dimension into a higher-level category, aggregating data in accordance with user-specified rules and producing a new dimension that organizes data into user-specified categories.


Sets are dynamic by default, as they can change when the underlying data changes. However, you can create static sets that remain fixed regardless of data updates.

Groups are static, maintaining them even when underlying data changes, but users have the option to manually adjust group members or create dynamic sets based on groups for more flexibility in analysis.

Use Cases

Sets are often used for highlighting specific data points in visualizations, certain custom filters, or performing conditional formatting.

Groups are employed when you want to aggregate or categorize dimension members for simplification or to create hierarchies.

19. What is a calculated field and How do we create it in Tableau?

A calculated field in Tableau is a user-defined field you construct by performing a calculation or formula on pre-existing fields in your dataset. You can use different string, logical, or mathematical operations to your data to produce fresh results or insights. For building unique measurements, dimensions, or aggregations that aren’t found in the original dataset, calculated fields are especially useful. Your capacity to properly analyze and visualize your data will be improved by using them to alter, manipulate, or derive new information from your data. To provide flexibility and customization to your data analysis process, calculated fields can be utilized in Tableau worksheets, dashboards, and reports.

To create a Calculated field in a Tableau, follow these steps:

  • Open the data source or the Tableau worksheet.
  • Right-click anywhere in the “data” window on the left and select “Create Calculated Field”.
  • Use fields, functions, and operators in the calculated field editor to create your own calculations.
  • To save the calculated field, select “OK”.

20. What are the different data aggregation functions in Tableau?

Tableau has many different data aggregation functions used in Tableau:

  • SUM: calculates the sum of the numeric values within a group or partition.
  • AVG: Computes the average of the numeric values.
  • MIN: Determines the minimum value.
  • MAX: Determines the maximum value.
  • COUNT: Count the number of records or non-null values.
  • VAR: Computes the variance of the sample population.
  • VARP: Computes the variance of the entire population.
  • STEDV: Compute the standard deviation of the sample population.
  • STEDVP: Calculate the standard deviation of the entire population.

21. What are the different types of charts available in Tableau?

Tableau offers a wide range of charts and different visualizations to help users explore and present the data effectively. Some of the charts in Tableau are:

  • Bar Chart: They can be used to compare values between categories or to demonstrate the distribution of data across categories. They help compare categorical data.
  • Line Chart: For displaying patterns and changes over time, line charts work incredibly well. To show how a single metric evolves, they are frequently used with time series data.
  • Area Chart: They are identical to line charts, however with an area chart, the area beneath the line is coloured. To highlight the contrasts between the variables, they are utilized with various multiple variables in the data.
  • Pie Chart: It displays pieces of an entire. They help demonstrate how data is distributed when each category represents a certain percentage of the total.
  • Tree Maps: They use layered rectangles to display hierarchical data. They are useful for illuminating hierarchical structures, such as those found in files or organizational directories.
  • Bubble chart: Bubble charts are useful for comparing and visualizing data points with three separate properties. They are in use when you want to highlight data clusters, demonstrate relationships, etc.
  • Scatter Plot: They are used to show how two continuous variables relate to one another. They aid in the data’s discovery of correlations, clusters, or outliers.
  • Density Map: The distribution and concentration of data points or values within a 2D space are depicted using density maps.
  • Heat Map: Data is displayed on a grid using heat maps, where colour denotes value. They can be used to visualize big datasets and spot patterns.
  • Symbol Map: By adding symbols or markers to a map to indicate information about particular locations, symbol maps are used to portray geographic data.
  • Gannt Chart: To visualize tasks, their durations, and dependencies over time, Gannt charts are used in project management.
  • Bullet Graph: They are used to monitor advancement toward a goal. They offer a convenient method of showing a measure, a target, and performance ranges.
  • Box Plot(Box and Whisker): They are employed to show the data’s distribution and spot outliers. The median, quartiles, and possible outliers are displayed.

22. What is a dual-axis plot and how we can create it in Tableau?

A dual-axis plot in Tableau is a visualization that combines two distinct chart types on one graph while employing two different y-axis. This makes it simpler to spot patterns and links between two sets of data that have various scales or units of measurement. Dual-axis plots offer a more thorough picture of the data in a single chart and help show data with many dimensions or metrics.

To create a dual-axis in Tableau, follow these steps:

  • Connect to the data source. Drag and drop the dimensions and measure into the “columns” and “rows” shelves, respectively, to create a chart.
  • Simply select “Duplicate” from the context menu when you right-click the chart. By doing this, the chart will be duplicated.
  • Change the measure you wish to show in the copied chart by dragging the new measure to the “columns” or “rows” shelf and replacing the current measure.
  • By selecting the “dual-axis” in the second chart, the measure can be assigned to a different axis. As a result, the chart will have two distinct axes.
  • Select “synchronize axis” by doing a right-click on one of the axes. Formatting, color, and label changes as necessary. You now have a chart with two axes.

23. How Can You Display the Top Five and Bottom Five Values in the Same View in Tableau?

In Tableau, to display the Top five and bottom five values, we need to follow some steps:

  • Create a calculated field using the following command:

RANK(SUM[measure], ‘asc’) <= [Parameter]


RANK(SUM[measure], ‘dsc’) <= [Parameter]

This calculation filters data in either ascending (‘asc’) or descending (‘dsc’) order, depending on whether the rank of the SUM of the measure is less than or equal to a given parameter.

  • To add a new field, drag it to the Filters shelf. For the Filter dialog to close, click OK.
  • Right-click the newly added field in the Filters shelf. Decide on Compute utilizing > Pane (Down).
  • Be sure to select True in the Filter dialog. Choose OK.

24. What Is the Difference Between Tableau Heat Map and Treemap?


Tree Maps

Heat Maps


Treemaps display hierarchical data in a rectangular, nested layout. Information is communicated through the size and color of each rectangle, each of which indicates a category or subcategory.

Heat maps show values in a grid by using color intensity. They are typically used to show how data points are distributed or concentrated in a 2D space.

Data Type

They are employed to show categorical and hierarchical data.

They’re employed to show continuous data, such as numerical numbers.

Color Usage

In order to depict a certain attribute or measure, color is widely employed in treemaps. Additional information can be conveyed through a color’s intensity.

Values are often represented in heat maps by the intensity of the colors. Higher values are represented by brighter or darker hues, whereas lower values are reflected by lighter colors.


With interactive tree maps, users may click on the rectangle to reveal subcategories and dig deeper into hierarchical data.

Users can hover over the cells on interactive heat maps to view particular numbers or features.


They are employed for category, hierarchical, and organizational data visualization.

They are utilized in a variety of industries, including finance, geospatial data, data analysis, and more.

25. What is the Level of Detail (LOD) Expression in Tableau?

Level Of Detail (LOD) Expression is a strong feature that lets you do computations within your data visualization at different degrees of granularity irrespective of the visualization’s dimensions and filters. Using LOD expressions will provide you greater power and versatility when disaggregating or aggregating data depending on the specific dimensions or fields.

There are three types of LOD:

  • Include LOD: Include LOD expressions allow you to include one or more dimensions in the aggregation while keeping others at the current level of detail, giving you the flexibility to control the granularity of your analysis.
  • Exclude LOD: Exclude LOD expressions enable you to exclude specific dimensions from the aggregation while keeping the rest at their current level of detail, helping you focus on the dimensions that matter most for your calculations.
  • Fixed LOD: Fixed LOD expressions let you specify a set of dimensions to include in the aggregation independently of the view, enabling precise control over which dimensions affect your calculation.

26. How Do You Handle Null Values in Tableau?

Handling null values is important for data accuracy and visualization clarity. Some of the ways to handle null values are:

  • Replace Null Values: We can replace null values by right click on the field containing null values, going to “Edit” then clicking “Replace Null”. Enter the desired replacement value and then click “OK”.
  • Filter out Null values: We can filter out null values by creating a filter to exclude null values from your visualization. Drag the field with null values to the “Filter” shelf and uncheck the “Null” option.
  • Handling Null Values in Calculations: Using Tableau functions like ‘ISNULL()” or “ZN()” in calculations to handle null values.

27. How do you concatenate two strings in Tableau?

We can concatenate two strings in Tableau by creating a calculated field using either the ‘CONCAT()’ function or the ‘+’ operator.

28. What is the purpose of the IF function in Tableau, and how is it used?

The IF function in Tableau is used to build calculated fields that test a given condition and return various values depending on whether it is true or false. This is a form of conditional logic. The IF function is valuable for introducing logic and control flow into your Tableau calculations, allowing you to tailor data processing and visualizations to your needs.

To use the IF function in Tableau:

  • To use the IF function, go to the “Analysis” menu, and select “Create calculated field”.
  • In the calculation editor, write the IF expression in the following format:

IF condition THEN result_when_true ELSE result_when_false END

  • Use IF to apply conditional formatting such as changing the color of data points based on condition or to create calculated fields for custom filters or dynamic aggregations.

29. How can you extract the year from a date field in Tableau?

To extract the year from a date field in Tableau, you can create a calculated field using ‘YEAR()’ function.

  • Create a calculated field and use the ‘YEAR()’ function to extract the year from your data field.

YEAR([Data Field])

30. How do you use the DATEADD function to add or subtract time from a date field?

The Tableau function DATEDD() increments a given date and returns a new date. The interval and the date part together define the increment. This function allows you to perform various date calculations and is used in tasks like creating rolling averages, calculating future dates, or aggregating data by time intervals. To use this function:

  • Create a calculated field. In the calculation editor, use the ‘DATEDD’ function to add or subtract time from a field. The syntax for this is as follows:

DATEDD (interval, number, date)

31. What is the difference between the COUNT and COUNTD functions in Tableau?




Definition “COUNT” is used to count the number of records or rows in a dataset. “COUNTD” stands for “Count Distinct” and is used to count a number of distinct values in a dataset.
Function It counts all the rows, including duplicates, and provides a simple count of how many records exist. It counts only unique values and eliminates duplicates, providing a count of the distinct values in a field.
Example ‘COUNT([Customer ID])’ will count the number of CUSTOMER IDs in the dataset, including duplicates. ‘COUNTD([Customer ID])’ ill count the number of unique customer IDs in the dataset, excluding duplicates.

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


Reference Bands

Bollinger Bands


Reference bands are used as horizontal lines or bands to denote significant reference levels or points, such as trendlines, moving averages, and support and resistance levels.

A statistical tool called Bollinger Bands is used to assess price volatility and spot possible overbought or oversold positions in a financial asset.


Typically, reference bands are drawn by hand or in accordance with particular technical analysis indications or chart patterns.

Bollinger Bands are made up of three lines: the middle band, which is typically a simple moving average, the upper band, which is the middle band plus a certain number of standard deviations, and the lower band, which is the middle band less that same number of standard deviations.


In order to assist traders in choosing when to enter or exit positions, they are used to indicate important price levels where strong buying or selling pressure may occur.

Bollinger Bands are a tool for displaying price volatility. When the price moves in close proximity to the upper band, it can be deemed overbought, and when it gets close to the lower band, it might be deemed oversold.


The degree to which reference bands can be altered depends on personal preferences and trading tactics.

In order to fit their trading methods, traders can change the parameters of Bollinger Bands, which have predetermined calculations based on the moving average and standard deviations.


Trading decisions are based on how traders interpret price changes in relation to these reference levels.

By examining how the price is positioned in relation to the bands, traders can utilize Bollinger Bands to spot potential reversals, breakouts, or trend strength.

Tableau Interview Questions for Experienced

33. How can you calculate the percentage of total for a field in Tableau?

To calculate the percentage of total for a field in Tableau. Choose percentages from the “Analysis” to display a variety of percentages of the row, table, row in the pane, table in the pane, and cell. Select the total value from which the percentage is to be determined after choosing one of the given options to calculate the percentage.

34. What is the purpose of the AVG function in Tableau, and how is it used?

The AVG function is used to calculate the average(mean) value of a numeric field within a dataset, it is used to analyze and visualize the central tendency of a dataset. Steps to do so:

Create a calculated field and in the calculated editor, use the AVG function to calculate the average of a numeric field.

AVG([Numeric Field)]

We can use the AVG function to display the average value in charts, graphs, or tables to understand the central tendency of a dataset or we can use it to compare the average values across different categories or time periods to identify trends or anomalies.

35. How can you use the RANK function to rank data in Tableau?

Create a worksheet, drag and drop the dimensions you want to rank the data and the measure in the marks card. 
In the “Analytics” pane on the left, find the “Rank” function and drag it onto your worksheet. 
Configure the RANK function calculation by right-clicking on it

36. How can you use the WINDOW_AVG function to calculate a moving average in Tableau?

To calculate a moving average using the ‘WINDOW_AVG’ function in Tableau:

  • Create a calculated field, in the editor, write the ‘WINDOW_AVG’ function to calculate the moving average. The function can be used as :

WINDOW_AVG([measure] , [start], [End])

  • To add the moving average to your visualization in Tableau, drag and drop the calculated field onto your worksheet and configure the calculation by right-clicking on it to access the “Edit Tableau Calculation” dialog.
  • To control the window size or the number of data points included in the moving average calculation, you can use the ‘[start]’ and ‘[end]’ arguments in the ‘WINDOW_AVG’ function.
  • After this, you can customize the format and interact with your visualization.

37. How can you use the WINDOW_SUM function in Tableau?

To compute a running or cumulative sum of a measure within a given window or range, use Tableau’s ‘WINDOW_SUM’ function. To implement it :

  • Create a calculated field, and in the editor write the ‘WINDOW_SUM’ function.

WINDOW_SUM(SUM([measure]), [start], [end])’

  • The optional arguments [Start] and [End] specify the window or range for the total. They can be configured to limit the scope of the calculation. Drag and drop the fields to the shelf to add visualization.

38. When we will use the SCRIPT_REAL functions in Tableau?

When you need to employ unique computations or Python or R scripts to manipulate and analyze your data, you would use Tableau’s ‘SCRIPT_REAL’ function. You can use this method to run outside scripts and get real (numeric) values that you can utilize in your Tableau graphic.

You can use SCRIPT_REAL in some scenarios like:

  • Advanced Statistical Analysis: If you need to use computations or statistical analysis that Tableau does not provide directly.
  • Data Transformation: when you want to use custom scripts to alter and preprocess your data before visualization.
  • Geospatial Analysis: for specialized geospatial research with third-party scripts or libraries.

39. How do you use the LOOKUP function in Tableau?

In Tableau, the LOOKUP function is used to locate a given dimension or measure value within the data. It is useful for comparing a data point to other data points at a given offset. The tableau LOOKUP function can used like this:

LOOKUP( expression, offset)

‘expression’: dimension or measure you want to retrieve from the data.

‘Offset’: specifies the relative position of the data point you want to look up.

Open the worksheet or workbook where you want to create your calculation using the LOOKUP function. Right-click on Data and select “Create Calculated field”. In the calculate editor, you can write your LOOKUP function.

40. How Do You Add a web page to a Tableau Dashboard?

You can integrate a Tableau dashboard or report into a web application or web page to build dynamic web pages with interactive Tableau visuals. You can include Tableau content in a web application using its embedding options and APIs.

To create a dynamic website in Tableau, follow these steps:

  • Click the webpage option under “Objects” on the dashboard.
  • Don’t input a URL and then click “OK” in the dialog box that appears.
  • By clicking the dashboard menu, select “Action.” To add an action, click the action’s ‘Add Action’ button and choose ‘Go to URL’.
  • Enter the website’s ‘URL’ and then click the arrow next to it. ‘OK’ should be clicked.

41. What are the different ways to optimize a Dashboard’s Performance?

For a dashboard to load quickly, be responsive, and offer a seamless user experience, its performance in Tableau must be optimized. Here are various methods for improving the functionality of a Tableau dashboard:

  • Data Source Optimization: Consider using data extracts (TDEs) when working with large datasets for faster query performance or apply data source filters to limit the amount of data retrieved from the source.
  • Data Aggregation: Use aggregation in your visualization and calculations to reduce the volume of data processed.
  • Parameter Optimization: Use parameters instead of quick filter when interactively is required but quick filters would slow down the dashboard.
  • Filter Optimization: Employ context filters, extract filters, and minimize quick filters.
  • Sheet optimization: Hide unused sheets, simplify visuals, and optimize filters.

42. How we will plot the geographical data in Tableau?

To plot geographical data in Tableau, follow these steps:

  • Connect to Data: Connecting to a dataset that contains latitude and longitude coordinates or location names that Tableau can geocode is the first step in using Tableau to see geographic data.
  • Drag and Drop Dimensions: Locate your geographic data’s dimensions in the Data pane (such as Country, City, Latitude, and Longitude) and drag them to the “Rows” or “Columns” shelf.
  • Choose a Map Visualization: Map visualizations offered by Tableau include “Symbol Maps,” “Filled Maps,” and “Density Maps.” Pick the one that best fits your objectives for data and visualization. For further control over what appears on the map, drag the geographical dimension to the “Detail” shelf.
  • Assign Measures: To encode data attributes onto the map, drag measures (such as sales, population, or temperature) to the “Color,” “Size,” or “Label” shelf.
  • Customize the Map: To change the map’s markers, labels, colors, and tooltips, use the “Marks” card. The map’s style, background, and layers can all be changed.

Scenario Based Tableau Interview Questions 

43. What type of chart would you use to visualize the quarterly sales trends for the last five years?

A line chart or time series line chart can be used for displaying quarterly sales patterns over the previous five years. A line chart makes it possible to compare sales patterns clearly between years since it shows each year’s quarterly sales data as a separate line. Using this type of graphic, you may spot trends, seasonality, and variations in sales performance over a five-year period. A Time Series Line Chart offers extra possibilities, such as trend analysis and forecasting, if you have a date dimension. These graphs provide insightful information on sales trends, making them crucial tools for performance evaluation and data-driven decision-making in corporate situations.

44. Which chart will you use to visualize the distribution of data across different quartiles?

A Box Plot, also known as a Box-and-Whisker Plot, is an effective visualization tool for comprehending data distribution over quartiles. It offers a succinct breakdown of the major statistics in a dataset. The graphic consists of a box with the median inside that symbolizes the interquartile range (IQR). To help spot outliers, the “whiskers” extend from the box to the minimum and maximum values inside a range. Box plots are great for displaying the central tendency, spread, skewness, and occurrence of extreme values in data. They are helpful for data analysis and statistical comparisons because they provide a rapid and meaningful perspective of how data is distributed across quartiles.

45. Which chart will you use to compare the market share of different companies in a specific industry?

To compare the market share of different companies in a specific industry, a Stacked Bar chart or a Group Bar chart is commonly used. These chart types allow you to visualize the market share of each company within the industry, making it easy to see how they compare to one another.

Stacked Bar chart: A stacked bar graph shows the evolution of a category’s entire market size. Each part shows the market share of a different company and is stacked. The percentage of the company’s market share is shown in segment height, effectively indicating market composition.

Group Bar Chart: A grouped bar graph groups bars for each period of time or category. With bars denoting several companies, each group denotes a time period or category. A company’s market share for that category is shown by the length of the bar, allowing for easy comparisons.

46. Which chart would be best to visualize the share price trends across the year of different companies of a specific industry?

The best option is a Multiple Line Chart or a Line Chart with Multiple Series to show share price patterns over the course of the year for many businesses in a certain industry. With the use of this chart type, you can compare the performance of various companies over time by plotting the share price movements for each firm on the same graph. You can see how the share prices of each line, which each represents a distinct firm, change and develop throughout the course of the year. When examining and contrasting the performance of various businesses operating in the same industry, this method is especially useful.

47. How can we visualize the multiple dimensional data like correlations or covariance in Tableau?

It might be difficult to visualize covariance or correlation between numerous dimensions in Tableau since these metrics frequently entail pairwise comparisons. To learn more about relationships, you can construct heatmaps and scatter plots. Here’s how:

  • Create a scatter plot matrix for pairwise comparisons.
  • Use a heatmap to represent relationships with color.
  • Calculate correlations using table calculations or custom formulas.
  • Add interactivity with parameters or filters.

48. What chart will be suitable to display the distribution of data points in a single variable?

A histogram is an appropriate graph to show how data points in a single variable are distributed. The frequency or count of data points inside predetermined intervals or bins is represented visually by a histogram. It enables you to observe any patterns or outliers, as well as the distributional shape of the data and central tendencies. For understanding the distribution of continuous or numerical data, histograms are especially helpful.

49. When we have data with a hierarchical structure, such as product categories and subcategories, which chart will be best suitable to show this hierarchy?

When you have hierarchical data structures like product categories or sub-categories, the best chart to show this hierarchy and the relationships between different levels is a TreeMap.

A TreeMap is a hierarchical data visualization that uses layered rectangles to show categories and subcategories. Rectangles are nested to indicate the hierarchy, with bigger rectangles signifying parent categories and smaller rectangles inside signifying subcategories. Each rectangle’s size gives quantitative information, and additional information can be encoded using color. The interactive nature of treemaps allows viewers to click on parent rectangles to explore subclasses.

50. What is a tableau reporting tool?

Tableau is a potent business intelligence (BI) and data visualization software program used to create interactive and shareable reports and dashboards. Users can connect to different data sources with it, transform unprocessed data into insightful visuals, and derive insights from their data. The user-friendly design of Tableau and its wealth of tools for data exploration, analysis, and storytelling are well-known. To transform data into usable insights, make data-driven choices, and effectively convey findings through interactive reports and dashboards, it is widely utilized in businesses across industries. The several editions of Tableau include Tableau Desktop (for authoring reports), Tableau Server (for sharing and collaborating on reports), and Tableau Online (a cloud-based version).

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In this article we have listed 50 top most asked Tableau interview questions and answers for freshers and experienced (basics to advance). Over the years careers in data visualization and data analysis have grown and the demands of good data analysts or BI experts are also growing parallelly.

So keep learning and keep practising the questions to crack any Tableau interviews.

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