Tableau has gained significant popularity in the field of data visualization and business intelligence. As a result, there are many openings for Tableau professionals who can create compelling visualizations and provide valuable insights. That’s why we are presenting this collection of the most commonly asked Tableau-related interview questions and answers found in job interviews to get you started. Keep reading to find out how you can perform well
The practice of data visualization is becoming crucial to bridge the gap between the human and a machine to mediate analytical insight in a productive way.
Almost 50% of Fortune 500 companies have started using Tableau. So the demand for skilled tableau professionals has been increasing over the years. So, if you wish to start your career in data visualization, then get trained from the MindMajix Tableau Training.
We have compiled here Frequently Asked Tableau Interview Questions and Answers. The questions presented in this blog are collected based on the opinions of tableau experts.
To make it easy and understandable format, we have divided these questions into three categories as Freshers, Experienced, and Real-time.
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Tableau is the most powerful and fastest visualizing tool that is used in the Business Intelligence(BI) Industry. It simplifies the raw data into an understandable format. Analysis of the data becomes faster with Tableau. The visualizations can be created in the form of dashboards. The visualizations or diagrammatic representation of data can easily be understood by the employees of the organizations who are at different levels.
Data visualization means the graphical representation of data or information. We can use visual objects like graphs, charts, bars, and a lot more. Data visualization tools provide an accessible way to see and understand the data easily.
Below are a few extensions in Tableau:
Tableau Desktop's latest version is 2021.3(as of, 7thSep 2021).
LOD Expression stands for Level of Detail Expression, and it is used to run complex queries involving many dimensions at the data sourcing level.
A heatmap is a graphical representation of data that uses the color-coding technique to represent different values of data. As the marks heat up due to their higher value, dark colors will be shown on the map.
TreeMap is a visualization that organizes data hierarchically and shows them as a set of nested rectangles. The size and colors of rectangles are respective to the values of the data points they project. Parent rectangles will be tiled with their child elements.
TreeMap Heat MapIt represents the data hierarchically and shows them as a set of nested rectangles. It represents the data graphically which uses multiple colors to represent different values. It is used for comparing the categories with colors, and size, and it can also be used for illustrating the hierarchical data and part-to-whole relationships. It is used for comparing the categories based on color and size. And also it is great in spotting patterns based on the density of the information.
The colors and size of rectangles are respective to the values of the data points When their values are higher or the density of records, the data will represent in dark color.
Parameters are dynamic values, we can replace the constant values in calculations.
Tableau supports below data types. Data TypeMeaningExamplesStringCharacter Sequence. Enclosed in ''.Tableau', 'World'Number (Whole)Integers9Number (decimal)Floating values.123.45BooleanThey are logical values.TRUE, FALSEDateDate"02/01/2015"Date & TJmeDate and Time01 January 2019 05:55:00 PMGeographic ValuesGeographical ValuesIndia, Italy, Canada
Tableau dashboard is a group of various views that allows you to compare different types of data simultaneously. Datasheets and dashboards are connected if any modification happens to the data that directly reflects in dashboards. It is the most efficient approach to visualize the data and analyze it.
[ Related Article: The Right Way to Build a Dashboard ]
Page shelf breaks the views into a series of pages. It displays an alternate view on each page. Due to this feature, you can analyze the effect of each field on the rest of the data in the view.
The story can be defined as a sheet which is a collection of series of worksheets and dashboards used to convey the insights of data. A story can be used to show the connection between facts and outcomes that impacts the decision-making process. A story can be published on the web or can be presented to the audience.
Facts are numeric measures of data. They are stored in fact tables. Fact tables store the type of data that will be analyzed by dimension tables. Fact tables have foreign keys associated with dimension tables.
Dimensions are descriptive attributes of data. Those will be stored in the dimensions table. For example, customer information like name, number, and email will be stored in the dimension table.
There are 2 connection types available in Tableau.
Extract: Extract is a snapshot of data that will be extracted from the data source and put into the Tableau repository. This snapshot can be refreshed periodically fully or incrementally. This can be scheduled in Tableau Server.
Live: It creates a direct connection to the data source and data will be fetched directly from tables. So, data will be up-to-date and consistent. But, this also affects access speed.
Tableau works the same as SQL. So, it supports all Joins possible in SQL
Data modeling is the analysis of data objects that are used in a business or other context and also used as identification of the relationships among these data objects. It is the first step of doing object-oriented programming.
Dual-axis is used to show 2 measures in a single graph. It allows you to compare 2 measures at once. Many websites like Indeed use this Dual-axis to show the comparisons and growth rate.
Multiple measures can share in a single axis so that all the marks will be shown in a single pane. We can blend measures by dragging the 1st measure on one axis and the 2nd on the existing axis.
Shelves: Every worksheet in Tableau will have shelves such as columns, rows, marks, filters, pages, and more. By placing filters on shelves we can build our own visualization structure. We can control the marks by including or excluding data.
Sets: The sets are used to compute a condition on which the dataset will be prepared. Data will be grouped together based on a condition. Fields which is responsible for grouping are known assets. For example – students having grades of more than 70%.
Whenever we set a context filter, Tableau generates a temp table that needs to refresh each and every time, whenever the view is triggered. So, if the context filter is changed in the database, it needs to recompute the temp table, so the performance will be decreased.
There is a card to the left of the view where we can drag fields and control mark properties like color, size, type, shape, detail, label, and tooltip.
When you are ready to make a data source available to other Tableau desktop users. You can publish it to the Tableau server or online. Or else you can make it available by saving the same like an embedded excel or text file.
Dual-axis is used to show 2 measures in a single graph. It allows you to compare 2 measures at once. Many websites like Indeed use this dual-axis to show the comparisons and growth rate.
A bullet graph is a variant of Bar graph. It is responsible for comparing the performance of one measure with other measures.
Gantt Chart displays the progress of value over the period. It consists of bars along with the time axis. It is a project management tool. Here, each bar is a measure of a task in the project framework.
A histogram chart shows the distribution of continuous information over a certain period of time. This chart helps us to find extreme points, gaps, unusual values, and more concentrated values.
In Tableau, there are no limitations to the file sizes. Moreover, there is no row or column limit to import the data.
Tableau Reader is a free desktop application, where you can read and interact with the Tableau packaged workbooks. It can only open the files but cannot create new connections to the workbook.
The published data source contains connection information that is independent of workbooks and can be used by multiple workbooks.
The embedded data source contains connection information but it is associated with the workbooks.
When we are working with large volumes of data, incredible data may be messed up. With Tableau, you can easily create hierarchies to keep your data neat. Even if you don’t need it, it is built into your data, which you can easily manage or organize the data and you can track the data easily.
A column chat visualizes the data as a set of rectangle columns, as their lengths are proportional to values when they represent the data. The horizontal axis shows the category to which they belong, and the vertical axis shows the values.
The bar chart visualizes the data as a set of rectangle bars, as their values are proportional to lengths when they represent the data. The vertical axis shows the category to which they belong to and the horizontal axis shows the values. So, the bar chart is a vertical version of the Column chart.
The line chart is a popular type of diagrammatic way for visualizing the data, it connects the individual data points to view the data. We can easily visualize the series of values, we can see trends over time or predict future values. The horizontal axis holds the category to which it belongs and the vertical axis holds the values.
Stacked Bar Chart, composed of multiple bars stacked horizontally, one below the other. The length of the bar depends on the value in the data point. A stacked bar chart makes the work easier, they will help us to know the changes in all variables presented, side by side. We can watch the changes in their total and forecast future values.
Stacked Column Chart, composed of multiple bars stacked vertically, one on another. The length of the bar depends on the value in the data point. A stacked column chart is the best one to know the changes in all variables. This type of chart should be checked when the number of series is higher than two.
An area chart is nothing but a line chart, the area between the x-axis and lines will be color or patterns. These charts are typically used to represent accumulated totals over time and are the conventional way to display stacked lines.
[ Check out Tableau Charts ]
Step 1: Go to public.tableau.com and enter your e-mail address and click “ Download the App “.
Step 2: After downloading the file, run the file and follow the prompts to install Tableau.
Step 3: Now, you can see the Tableau shortcut on your desktop.
Step 4: Double click on the icon, to load Tableau public. Now you see the screen below.
Context Filters are applied to the data rows before any other filters. They are limited to views, but they can be applied on selected sheets. They define Aggregation and Disaggregation of data in Tableau
Step 1: Drag the subcategory dimensions to the row shelf and measure sales to the column shelf. Now choose the horizontal bar chart as chart type and again drag the sub-category dimensions to the filter shelf. Then we will get the following chart.
Step 2: Right-click on the Sub-Category field in the filter shelf and go to the Top fourth tab. Choose the option field, from the next drop-down and choose the option Top 10 by Sales Sum as shown in the following screenshot.
Step 3: Drag the dimension Category to the filter shelf. Right-click on the general tab to edit and under that choose Furniture from the list. As you can see the result shows three subcategories of products.
Step 4: Right-click the Category: Furniture filter and select the option Add to Context. This produces the final result, which shows the subcategory of products from the category Furniture which are among the top 10 subcategories across all the products.
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Tableau has 4 main products.
Filters are the simpler and more straightforward feature in Tableau. It applies to dimensions or measures directly. For example, to only show Gujarat or Karnataka in a State dimension, we can apply the filter on that. In Tableau, there are multiple UI options available for filters like radio buttons, drop-down lists, checkboxes, sliders, and more. Filters on sheets are also available in Tableau.
Parameters are like variables. They are complex and more powerful. Like a variable, a parameter can be used in calculations. So, that means, it only allows a single value. Parameters have the same UI options except for checkboxes because checkboxes don’t have a single value. For example, we can create a parameter for interest rate and period, and then we can use these parameters to calculate interest and principal payments.
Filters are used to provide the correct information to viewers after removing unnecessary data. There are various types of filters available in Tableau.
In a tiled layout, items don’t overlap. The layout will be adjusted according to the dashboard size. In the floating layout, items can be placed on some other layers. Floating items can have fixed positions and sizes.
Dimensions are divided into 9 various categories
Slowly ever-changing dimension: The value of the dimension changes over an amount of time for slowly ever-changing dimensions.
Example – student of worker
Chop-chop ever-changing Dimension: Value in the dimension is rapidly changing for chop-chop ever-changing dimensions.
Example – Age (It changes every second)
Unchanged Dimension: Values are constant for unchanged dimensions.
Example – Traffic Signals
Shrunken Dimension: A set of 1 dimension is termed as Shrunken Dimension.
Example – A week is Shrunken dimension for the month
Junk Dimension: Junk values or unrelated dimensions are termed as Junk Dimension.
Conformed Dimension: If any dimension is provided by various business areas, then such a dimension is termed a Conformed Dimension.
Example – Time (9-5) for any company or hospital or college
Degenerated Dimension: Degenerated dimensions have primary keys only without any matter of info.
Role enjoying Dimension: If one dimension is employed in multiple roles, then they are termed as Role enjoying Dimensions.
Example – Date for e-commerce site order (Date of Order, Date of Shipment, Date of delivery)
Inferred Dimension: Empty dimensions are called inferred dimensions. They are usually used in ETL.
Example – Customer email which he may not enter while submitting any form will be filled as null.
VIZQL is Visual Inquiry Language. It is a combination of VIZ and SQL. It is similar to SQL language. But instead of SQL commands, the VIZQL language converts data queries into visual images.
Aggregation → The process of summarizing the data and viewing a single numeric value is called aggregation. Example – sum/avg of salary for each employee
Disaggregation →The process of viewing each transaction for analyzing all the measures both dependently and independently. Example – individual salary transactions for each employee.
The dashboard consists of 5 components.
Discrete data roles consist of values that are separate and distinct. Discrete data roles can take individual values within a range. For Example – cancer patients in the hospital, no. of threads in a sheet, state. Discrete values are displayed as blue icons in the data window and blue pills on shelves. Discrete fields can be sorted.
Continuous data roles consist of any value within the finite or infinite intervals. For Example – age, unit price, order quantity. Continuous values are displayed as green icons in the data window and green pills on shelves. Continuous fields cannot be sorted.
Traditional BI Tableau BI Architecture has hardware limitations. Tableau does not have dependencies. It does not support in-memory, multi-thread, and multi-core computing. It supports memory when using advanced technologies. It has a predefined view of data. It uses predictive analysis for various business operations. We should need a good knowledge of BI and skills. It is easy to work and understanding without the knowledge of BI and the skills data security is provided data security is not provided for the public, whereas in the professional version.
[ Check out Date Functions in Tableau ]
We can check the performance of Tableau in the following 2 ways.
.twb: .twb means Tableau workbook. .twb is an XML sheet, that stores the data about your documents, stories, and dashboards. This file is the reference to the source file such as Excel or tde. This file will be linked to your source file when you save the TWB file. If you want to share your workbook you need to send both the workbook and data source file.
.twbx: It is a compressed file, where you have all files. It includes data source files, twb, and other files to produce the workbook. TWBX is obsolete for sharing because it will share the copy of the file instead of an original source file. .twbx is used for reports and we can view them using the Tableau viewer.
Step 1: Select Analysis -> drop down will open -> Select Create calculated field
Step 2: The Calculation Editor Box will open, and give the name to the calculated field.
Step 3: Enter a formula in the calculation editor.
Example: Sum(Profits)/Sum(Sales). (Calculation Editor validates the formula)
Step 4: Click, OK.
Now, the new calculated field added to the data pane.
Tableau dashboard allows the representation of parameters in four ways only. They don’t allow any multiple values like a filter can do. They only allow a single value.
The following are the reasons for low performance
Following are a few ways to improve the performance
Tableau Desktop Log files are placed in C: UsersMy DocumentsMy Tableau Repository. In case of live connection to any data source, check the log file “log.txt” and “tabprotosrv.txt” files. In case of extract connection to any data source, check the “tdeserver.txt” file which has detailed information about queries.
If the owner of a published workbook license expires then his/her role will change to “Unlicensed”. He/She cannot access those workbooks, but others can. Only site admin can change the ownership of those workbooks.
Follow few steps
Extract connection is better than live connection because extract connection can be used from anywhere, anytime without connecting to the database. We can construct our own visualizations on it irrespective of the database connection.
Versioning of workbooks can be done in 2 ways in Tableau.
Global filters can be applied to sheets, stories, and dashboards.
To add custom color in Tableau, we need to follow 3 steps
Cascading filters mean filter2 values are dependent on filter1 values. For Example, filter1 is country and if we select “India” for filter1, filter2 values should show all Indian states. This feature we can achieve by using the option “Only Relevant Values”.
To achieve this, we need to create 2 views
Below are a few charts that we should avoid.
Tableau cannot plot null values on the-axis. So, it will display an indicator at the lower right corner of the view. Once you click on that indicator, you have options to handle null values. Below are the options available to handle null values.
Yes, Tableau Public can only allow 10 million rows to users for data visualization.
Related Article: Create Pie charts, Scatter Plot, Area Fill charts & Circular View in Tableau |
We can download views or workbooks from the server. But, data formats available to us depend on the permissions granted by site administrators or content owners.
We can also download selected sheets into PDF format, but while generating PDF, web page objects won’t be included.
Yes, we can use unused columns in tableau filters.
Let us consider one example.
In the data source, I have columns like emp_id, emp_name, emp_sal, emp_dep, and emp_designation. But, in reports, I am using emp_name in columns and emp-sal in rows. I can use emp_designation on filters.
Extract files can be used without any connections and you can build your own visualization without connecting to the database.
We can join 32 tables in Tableau.
Yes, we can place an excel file in a shared location and we can use it to develop a report, but for better performance, we need to extract the file.
Yes, we can do testing in Tableau by using tools and the easiest way is using the desktop application. We need to check it before we publish it on the Tableau server.
Tableau, currently not supporting the multi-valued parameters. As Tableau parameters are not dynamic, we cannot filter the list of values at runtime.
If you want to show the profit and sales of each and every city under the state in the same worksheet, then follow a few steps.
The data which you want to display under the state, it must be in the same worksheet.
In the View, Size indicates the Sales, and Color indicates the profit of the respective state(which you have selected).
Tableau does not have any security permissions or to protect the data in Tableau public. Whatever we shared in Tableau public those files, workbooks can be viewed by all users. There is no security option in Tableau public.
Tableau public is like a repository, if you delete anything in the Tableau public the data will be lost, even if links are in other locations and blogs. We cannot access those links.
Yes, we can create relational joins in Tableau without creating a new table
It happens when the user is trying to publish the workbook which is connected to the internal or local server that means the company’s network.
Yes, Parameters have their own drop-down list, which enables the users to view the data entries which are available in the parameter during the creation.
Option 1:
We can create the group by using the calculated field.
Example:
IF [Container]=’Jumbo Box’ then ‘Big Containers’
ELSEIF [Container]=’Jumbo Drum’ then ‘Big Containers’
ELSEIF [Container]=’Large Box’ then ‘Big Containers’
ELSEIF [Container]=’Medium Box’ then ‘Midsize Containers’
ELSEIF [Container]=’Wrap Bag’ then ‘Midsize Containers’
ELSEIF [Container]=’Small Box’ then ‘Little Containers’
ELSEIF [Container]=’Small Pack’ then ‘Little Containers’
END
The above calculation creates the group with four values: Little Containers, Big Containers, Small Containers, Midsize Containers.
Option 2:
Create a set from the group, and use the set in the calculated field.
Step 1: Right-click on the Data Pane and then select Create Set.
Step 2: Create a set dialogue box that will open,
Enter the field name.
Select the group, on the general tab.
Step 3: Click Ok.
Yes, Tableau can be installed on both the Windows Operating system and macOS.
When we are publishing the reports to Tableau Server, there we will find an option to schedule the report, just select the time when you want to refresh the data.
Native Database gives the best performance when connected live.
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Whenever we set a context filter, Tableau generates a temp table that needs to refresh each and every time the view is triggered. So, if the context filter will be changed, the database needs to recompute and rewrite the temp table, which in turn slows down the performance.
There is a card to the left of the view where we can drag fields and control mark properties like color, size, type, shape, detail, label, and tooltip.
The published data source has connection information in it. It is independent of any workbook and can be accessed by multiple workbooks.
Multiple measures can share a single axis so that all the marks will be shown in a single pane. We can blend measures by dragging the 1st measure on one axis and the 2nd on the existing axis.
Yes, we can. Navigate to filter→ Right-click on it→ select customize→ uncheck the option “Show All”
A bullet graph is a variant of a Bar graph. It is responsible for comparing the performance of one measure with other measures.
Gantt Chart displays the progress of value over the period. It consists of bars along with the time axis. It is a project management tool. Here, each bar is a measure of a task in the project framework.
A histogram chart shows the distribution of continuous information over a certain period of time. This chart helps us to find extreme points, gaps, unusual values, and more concentrated values.
Tableau Public is an open-source and free service that allows anyone to publish the data source and visualizations to the web. These visualizations can then be embedded into blogs or web pages. They can also be distributed through email or social media. Moreover, they can be made downloadable by other end users. For Tableau Public, no programming skills are needed. It can be accessed by anyone free of cost.
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Usha Sri Mendi is a Senior Content writer with more than three years of experience in writing for Mindmajix on various IT platforms such as Tableau, Linux, and Cloud Computing. She spends her precious time on researching various technologies, and startups. Reach out to her via LinkedIn and Twitter.