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In this Tableau interview questions blog, I have collected the most frequently asked questions by interviewers. These questions are collected after consulting with top industry experts in the field of Data analytics and visualization. If you want to brush up with the Tableau basics, which I recommend you to do before going ahead with this Tableau Interview Questions, take a look at this blog.
In case you have attended a Tableau interview in the recent past, do paste those Tableau interview questions in the comments section and we’ll answer them ASAP. You can also comment below if you have any questions in your mind which you might face in your Tableau interview. In the meantime, maximize the data visualization career opportunities that are sure to come your way by taking Tableau online training with Edureka. You can even get a Tableau certification after the course. Click below to know more.
This Tableau Interview questions is divided into the following parts:
Let’s begin this Tableau Interview Questions with Beginners level questions first.
|Traditional BI Tools||Tableau|
|1. Architecture has hardware limitations.||1. Do not have dependencies.|
|2. Based on a complex set of technologies.||2. Based on Associative Search which makes it dynamic and fast|
|3. Do not support in-memory, multi-thread, multi-core computing.||3. Supports in memory when used with advanced technologies.|
|4. Has a predefined view of data.||4. Uses predictive analysis for various business operations.|
Here is the Tableau Product family.
It is a self service business analytics and data visualization that anyone can use. It translates pictures of data into optimized queries. With tableau desktop, you can directly connect to data from your data warehouse for live upto date data analysis. You can also perform queries without writing a single line of code. Import all your data into Tableau’s data engine from multiple sources & integrate altogether by combining multiple views in a interactive dashboard.
It is more of an enterprise level Tableau software. You can publish dashboards with Tableau Desktop and share them throughout the organization with web-based Tableau server. It leverages fast databases through live connections.
This is a hosted version of Tableau server which helps makes business intelligence faster and easier than before. You can publish Tableau dashboards with Tableau Desktop and share them with colleagues.
It’s a free desktop application that enables you to open and view visualizations that are built in Tableau Desktop. You can filter, drill down data but you cannot edit or perform any kind of interactions.
This is a free Tableau software which you can use to make visualizations with but you need to save your workbook or worksheets in the Tableau Server which can be viewed by anyone.
Tableau supports the following data-types:
Measures are the numeric metrics or measurable quantities of the data, which can be analyzed by dimension table. Measures are stored in a table that contain foreign keys referring uniquely to the associated dimension tables. The table supports data storage at atomic level and thus, allows more number of records to be inserted at one time. For instance, a Sales table can have product key, customer key, promotion key, items sold, referring to a specific event.
Dimensions are the descriptive attribute values for multiple dimensions of each attribute, defining multiple characteristics. A dimension table ,having reference of a product key form the table, can consist of product name, product type, size, color, description, etc.
The joins in Tableau are same as SQL joins. Take a look at the diagram below to understand it.
You can join a maximum of 32 tables in Tableau.
We can either connect live to our data set or extract data onto Tableau.
The benefit of Tableau extract over live connection is that extract can be used anywhere without any connection and you can build your own visualization without connecting to database.
They are Named areas to the left and top of the view. You build views by placing fields onto the shelves. Some shelves are available only when you select certain mark types.
Sets are custom fields that define a subset of data based on some conditions. A set can be based on a computed condition, for example, a set may contain customers with sales over a certain threshold. Computed sets update as your data changes. Alternatively, a set can be based on specific data point in your view.
A group is a combination of dimension members that make higher level categories. For example, if you are working with a view that shows average test scores by major, you may want to group certain majors together to create major categories.
A hierarchical field in tableau is used for drilling down data. It means viewing your data in a more granular level.
Tableau server acts a middle man between Tableau users and the data. Tableau Data Server allows you to upload and share data extracts, preserve database connections, as well as reuse calculations and field metadata. This means any changes you make to the data-set, calculated fields, parameters, aliases, or definitions, can be saved and shared with others, allowing for a secure, centrally managed and standardized dataset. Additionally, you can leverage your server’s resources to run queries on extracts without having to first transfer them to your local machine.
Tableau Data Engine is a really cool feature in Tableau. Its an analytical database designed to achieve instant query response, predictive performance, integrate seamlessly into existing data infrastructure and is not limited to load entire data sets into memory.
If you work with a large amount of data, it does takes some time to import, create indexes and sort data but after that everything speeds up. Tableau Data Engine is not really in-memory technology. The data is stored in disk after it is imported and the RAM is hardly utilized.
In Tableau, filters are used to restrict the data from database.
The different filters in Tableau are: Quick , Context and Normal/Traditional filter are:
Take a look at the example below:
Dual Axis is an excellent phenomenon supported by Tableau that helps users view two scales of two measures in the same graph. Many websites like Indeed.com and other make use of dual axis to show the comparison between two measures and their growth rate in a septic set of years. Dual axes let you compare multiple measures at once, having two independent axes layered on top of one another. This is how it looks like:
A heat map can be used for comparing categories with color and size. With heat maps, you can compare two different measures together.
A tree map also does the same except it is considered a very powerful visualization as it can be used for illustrating hierarchical data and part-to-whole relationships.
The process of viewing numeric values or measures at higher and more summarized levels of the data is called aggregation. When you place a measure on a shelf, Tableau automatically aggregates the data, usually by summing it. You can easily determine the aggregation applied to a field because the function always appears in front of the field’s name when it is placed on a shelf. For example, Sales becomes SUM(Sales). You can aggregate measures using Tableau only for relational data sources. Multidimensional data sources contain aggregated data only. In Tableau, multidimensional data sources are supported only in Windows.
According to Tableau, Disaggregating your data allows you to view every row of the data source which can be useful when you are analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine what age participants were most satisfied with the product.
Data extracts are the first copies or subdivisions of the actual data from original data sources. The workbooks using data extracts instead of those using live DB connections are faster since the extracted data is imported in Tableau Engine.After this extraction of data, users can publish the workbook, which also publishes the extracts in Tableau Server. However, the workbook and extracts won’t refresh unless users apply a scheduled refresh on the extract. Scheduled Refreshes are the scheduling tasks set for data extract refresh so that they get refreshed automatically while publishing a workbook with data extract. This also removes the burden of republishing the workbook every time the concerned data gets updated.
Viewing underlying SQL Queries in Tableau provides two options:
Performance testing is again an important part of implementing tableau. This can be done by loading Testing Tableau Server with TabJolt, which is a “Point and Run” load generator created to perform QA. While TabJolt is not supported by tableau directly, it has to be installed using other open source products.
In some cases, you can improve query performance by selecting the option to Assume Referential Integrity from the Data menu. When you use this option, Tableau will include the joined table in the query only if it is specifically referenced by fields in the view.
If data resides in a single source, it is always desirable to use Joins. When your data is not in one place blending is the most viable way to create a left join like the connection between your primary and secondary data sources.
Data blending is the ability to bring data from multiple data sources into one Tableau view, without the need for any special coding. A default blend is equivalent to a left outer join. However, by switching which data source is primary, or by filtering nulls, it is possible to emulate left, right and inner joins.
In Tableau, measures can share a single axis so that all the marks are shown in a single pane. Instead of adding rows and columns to the view, when you blend measures there is a single row or column and all of the values for each measure is shown along one continuous axis. We can blend multiple measures by simply dragging one measure or axis and dropping it onto an existing axis.
A story is a sheet that contains a sequence of worksheets or dashboards that work together to convey information. You can create stories to show how facts are connected, provide context, demonstrate how decisions relate to outcomes, or simply make a compelling case. Each individual sheet in a story is called a story point.
There are two types of data roles in Tableau – discrete and continuous dimension.
There are many ways to create story in Tableau. Each story point can be based on a different view or dashboard, or the entire story can be based on the same visualization, just seen at different stages, with different marks filtered and annotations added. You can use stories to make a business case or to simply narrate a sequence of events.
Tableau Drive is a methodology for scaling out self-service analytics. Drive is based on best practices from successful enterprise deployments. The methodology relies on iterative, agile methods that are faster and more effective than traditional long-cycle deployment.
A cornerstone of this approach is a new model of partnership between business and IT.
By adding the same calculation to ‘Group By’ clause in SQL query or creating a Calculated Field in the Data Window and using that field whenever you want to group the fields.
The difference between published data source and embedded data source is that,
Different Tableau files include:
You can embed interactive Tableau views and dashboards into web pages, blogs, wiki pages, web applications, and intranet portals. Embedded views update as the underlying data changes, or as their workbooks are updated on Tableau Server. Embedded views follow the same licensing and permission restrictions used on Tableau Server. That is, to see a Tableau view that’s embedded in a web page, the person accessing the view must also have an account on Tableau Server.
Alternatively, if your organization uses a core-based license on Tableau Server, a Guest account is available. This allows people in your organization to view and interact with Tableau views embedded in web pages without having to sign in to the server. Contact your server or site administrator to find out if the Guest user is enabled for the site you publish to.
You can do the following to embed views and adjust their default appearance:
falsein the code.)
According to your question you must have state, city, profit and sales fields in your dataset.
Step 1: Double click on the state field
Step 2: Drag the city and drop it into Marks card.
Step 3: Drag the sales and drop it into size.
Step 4: Drag profit and drop it into color.
Step 5: Click on size legend and increase the size.
Step 6: Right click on state field and select show quick filter.
Step 7: Select any state now and check the view.
Here is an example of refreshing the dashboard for every 5 seconds.
All you need to do is replace the api src and server url with yours.
If your server license expires today, your username on the server will have the role ‘unlicensed’ which means you cannot access but others can. The site admin can change the ownership to another person so that the extracts do not fail.
Yes! For sure. It gives you data insight to the extent that other tools can’t. Moreover, it also helps you to plan and point the anomalies and improvise your process for betterment of your company.
Yes, we can do it. But for better performance we should use Extract.
Yes, Tableau Desktop can be installed on both on Mac and Windows Operating System.
Tableau is not restricted by the no. of rows in the table. Customers use Tableau to access petabytes of data because it only retrieves the rows and columns needed to answer your questions.
This happens when a user is trying to publish a workbook that is connected to an internal server or a file stored on a local drive, such as a SQL server that is within a company’s network.
I hope that this Tableau Interview Questions were helpful to you. I will be coming up with more blogs on Tableau for you all very soon.
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