Tableau Interview Questions and Answers
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Best Tableau Interview Questions and Answers
Tableau and the concepts of data visualization is now highly used to bridge the gap between a highly advanced machine and human to analyze data insights in the most proactive and efficient way. In today’s digital world, it is estimated that nearly 500 top multinational companies are using Tableau. And, this why there is a huge demand for professional and certified Tableau experts. Are you interested in setting up your career in the field of Tableau? Then this top 50 Tableau interview questions and answers will help you in your preparation.
Here, we have compiled the most high priority Tableau interview questions that will make your preparation easier and effective. Every fresher and professional Tableau experts can use these top 50 Tableau interview questions and answers to build their career. Also, Tableau is one of the highly paying fields which will give you an incredible productivity in future. We have covered almost every topic in Tableau, these 50 interview questions will surely brush up your Tableau skills and will make you stand out in the interview. We wish you all success. Just go through all the top 50 Tableau interview questions and answers and make excellence in your future career.
Tableau which is a quickest and powerful visualizing tool is highly used in the field of Business Intelligence. A raw data can be simplified or extracted into an understandable data by Tableau which makes analysis of data quicker. The data visualization in Tableau can be in the form of dashboards which can be easily understood by the employees working at several levels.
Any data present in a database, an on-premise database, cloud application, excel file or in a data warehouse, can be easily analyzed with the help of Tableau. We can easily generate views through Tableau which can be shared with partners, colleagues and customers effectively. With Tableau, we can merge data together and keep them automatically updated.
QlikView | Tableau |
It grants good data integration | Tableau provides exceptional data integration |
It is good to work with multidimensional data | It is very good with multidimensional data |
It does not support powerpoint | It supports powerpoint |
Scalability is limited by RAM | It ensures maximum scalability |
Actually in Tableau, there is no limitation to file size and there is also no limitation to the number of rows and columns that are in line with data import.
The 5 main products provided by Tableau are as follows:
- Tableau Desktop
- Tableau Server
- Tableau Online
- Tableau Reader
- Tableau Public
Some of the Tableau file extensions are listed below:
- Tableau Workbook (.twb)
- Tableau Data extract (.tde)
- Tableau Datasource (.tds)
- Tableau Packaged Datasource (.tdsx)
- Tableau Bookmark (.tbm)
- Tableau Map Source (.tms)
- Tableau Packaged Workbook (.twbx) – It is a zip file that consists of both .twb and external files
- Tableau Preferences (.tps)
The latest version of Tableau Desktop as of November 6, 2019 is 2019.4
The process that is effectively used to communicate data or information by encoding it in the form of visual objects that are contained in graphics is known as data visualization.
A filter actually displays the exact data we are looking for by restricting the unnecessary data and the types of filters available in Tableau are as follows:
- Quick Filter
- Context Filter
- Datasource Filter
At the time when a context filter is generated by Tableau, a temporary table is also created for the specific filter set where the other filters in the form of cascade parameters will be applied on the context filter.
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Frequent changes are not allowed in context filter because if the context filter is changed by the user then the database and the temporary table has to be recomputed and rewritten respectively this will actually slow down the performance.
Level of Detail Expression (LOD) is used to perform complex queries that consist of several dimensions and present in the various data sourcing levels.
A graphical representation of data that makes use of the color coding technique to portray the values of data is known as heat data. The heat map will represent a dark color, if the marks are heated up because of its higher value.
A type of visualization that organizes the hierarchy of data and displays them in the form of nested rectangle is known as the tree map. The color and the size of the nested rectangles are because of the values of the data points.
- Firstly, right click on the filter
- The choose the customize option
- Now you will have to uncheck the show all option
- Now, the show all option will be removed from the Tableau auto filter.
Parameters in Tableau are the dynamic values with we can change or replace any of the constant values present in the calculations.
Yes, parameters in Tableau have an own drop-down list. The entries made in the parameters can be viewed in the drop-down list.
Some of the data types that are supported in Tableau are as follows:
- String
- Number (Whole, Decimal)
- Boolean
- Only Date or Date & Time
- Geographic Values
Tableau dashboard consists of several types of views with which you can compare several data types effectively. Dashboards are connected with datasheets so that the changes made in any data are immediately reflected in the dashboard easily. Tableau dashboard is actually an efficient approach to analyze and visualize data at ease.
The one that is used to break views into several series of pages is known as page shelf that displays an alternative view on each of the pages. With page shelf, we can analyze the performance of each field present in the data of each view.
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A collection of worksheets and dashboards that are used to display the insights of data accurately is known as the story. It actually shows the relation between the facts and the outcomes that is in relation with the decision making process. It can be presented to the audience or it can be published on the web.
The numeric values of data known as facts are often stored in the facts table. The data which are analyzed by dimension tables are mostly stored in the facts table. They have some of the foreign keys that are duly associated with the dimension table.
The descriptive attributes of data known as dimensions which can be in the form of name, email, and mobile number of the customer are stored in the dimension table.
The two main connection types present in Tableau are as follows:
- Extract
- Live
A snapshot of the data extracted from the data source and transferred to the Tableau repository is known as the extract. By scheduling in the Tableau server, we can automatically refresh the snapshots.
Live actually establishes a direct connection with the data source and the data present can be extracted directly from the tables. In this manner, the data will be consistently refreshed and updated regularly. And, this process is also meant to affect the access speed.
Listed below are some of the methods which can be used to improve the performance of Tableau:
- With the help of extract, we can make workbooks perform quicker
- To reduce the volume of data we will have to reduce the scope of data
- The volume of marks on the view has to be reduced in order to avoid information overload
- Use integers or Booleans to calculate as this will be quicker than strings
- Use context filters and hide unused fields
- Make use of some of the alternative ways apart from filters to obtain the same deserving result
- Avoid unnecessary filters, sheets and calculations
- Make use of indexing in tables and prefer similar fields for filtering
Tableau is similar to SQL and the types of joins present in Tableau are as follows:
- Left outer join
- Right outer join
- Full outer join
- Inner join
Yes, exactly we can use the non-used columns that are not used in reports but used in data source in Tableau filters.
With Tableau extract file, we can build our own desired visualizations without connecting to any of the databases.
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Only a maximum of 32 tables can be joined in Tableau and tables more than 32 cannot be joined.
- Instant feature deliveries
- Operating environment is highly stable
- Rather than maintain and fix, you will have more time to add value
- Joins can be performed accurately in two different ways:
- Join can be made of common columns
- Join can also be done by common data types
If equality operator is used in the join condition, then such type of joins are known as equi joins in Tableau.
If the join to a table is performed by itself then it can be termed as self-join in Tableau.
If operators apart from equality is used in the join condition, then such type of joins are known as equi joins in Tableau.
The process of mixing data from different data sources and allowing the users to perform the analyses in a single data sheet is known as data blending.
There are two ways via which we can perform data blending at ease and they are:
- Automatic way
- Custom or Manual way
Some of the rules that have to be followed in order to attain data blending at ease are as follows:
- To perform data blending between the two data sources those data sources should a dimension in common
- Also, in that common dimension there should be at least single matching value
Yes, we can perform the above mentioned activity but to attain better performance, we can consider using an extract.
.twb file extension is actually a live connection which directly points a data source; any user who received files in this format will need required permission to access such data source.
.twb file extension will take the data offline and will store it in the form of a package or zip-like file, thus the need for access permission is eradicated.
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In order to display two measures in a single graph, tableau makes use of dual axes.
In blended axis all the measure will be displayed in a single axis and all the marks will be denoted in a single pane.
As Tableau is data visualization software, we cannot perform testing.
In Tableau, we can make use of parameters with auto-updates, measure-swaps, calculated fields, changing views, filters and actions.
New custom SQL query is written in Tableau in order to pull the already connected data in an accurate structured view. This will increase the performance of Tableau automatically.
Yes, Tableau is good for strategic acquisition as it gives data insights clearly than the others. Tableau assists us in accurately planning and pointing the anomalies and improvising the entire process for betterment.
With the help of calculated fields or filter in Tableau, we can easily list the top 5 and the last 5 sales in the same view.
The steps involved are as follows:
- Firstly, consider connecting that data twice, initially for the database and then for the flat file, then choose edit relations from the data.
- Then give a join condition in the common column available in the database to the flat file.
The performance of Tableau is interrelated with the performance of data source; if more time is taken by the data source to execute a query, then it is certain that Tableau will have to wait until that.
The major difference between Tableau 7.0 and Tableau 8.0 are as follows:
- In the recent update there are many new visualizations like bubble chart, whisker plot, tree map and box
- With the latest upgrade, we can easily copy worksheets from one workbook to another
- R script is also introduced in the new version
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