Tableau is a business intelligence software that visually represents data from varied sources to create interactive and shareable dashboards.
This tool has made the entire process of analyzing data and questioning your product-market fit, easier. It has various in-built features for data exploration without getting overwhelmed by the software elements.
Some of the advantages of using Tableau
Data visualization: Rather than having complex computations over an Excel sheet, Tableau provides beautiful insights, data blending, and dashboarding derived from the data.
Create interactive visualizations: Tableau provides a drag-n-drop facility to quickly let the users interact with the data. You can check some of the templates created using tableau in the tableau gallery.
With Tableau’s gallery of templates, you can choose your option and customize it. With data visualization
features, you can easily embed tons of information in the form of infographics that appeals to the audience.
Ease of implementation: With drag-n-drop options, Tableau is reportedly easier to use. This is one such tool that you can learn without having any coding background or experience in Python, Business objects, or DOMO.
Handle large amounts of data: Tableau is competent enough to handle millions of rows without affecting the dashboard performance.
Integration of scripting languages: With Tableau, you can perform complex data computations using scripting languages like Python and R by importing some visuals or packages.
With much hype around data analytics and visualization, it is important to get well-versed with the tools simplifying the data journey. We have curated a list of interview questions ranging from beginner’s level to expert to help you land a job in your preferred expertise.
Data visualization is a way to represent data that is visually appealing and interactive. With advancements in technology, the number of business intelligence tools has increased which helps users understand data, data sets, data points, charts, graphs, and focus on its impact rather than understanding the tool itself. The basic difference between the traditional BI tools and Tableau lies in the efficiency and speed. Tableau like other BI tools has a range of
products: The parameter is a variable (numbers, strings, or
date) created to replace a constant value in calculations, filters, or reference lines. For example, you create a field that returns true if the sales are greater than 30,000 and false if otherwise. Parameters are used to replace these numbers (30000 in this case) to dynamically set this during calculations. Parameters allow you to dynamically modify values in a calculation. The parameters can accept values in the following options: In Tableau, when we connect to a new data source, each field in the data source is either mapped as measures or dimensions. These fields are the columns defined in the data
source. Each field is assigned a dataType (integer, string, etc.) and a role (discrete dimension or continuous measure). Measures contain numeric values that are analyzed by a dimension table. Measures are stored in a table that allows storage of multiple records and contains foreign keys referring uniquely to the associated dimension tables. While Dimensions contain qualitative values (name, dates, geographical data) to define comprehensive attributes to categorize, segment, and
reveal the data details. Tableau’s specialty lies in displaying data differently either in continuous format or discrete. Both of them are mathematical terms used to define data where continuous means without interruptions and discrete means are individually separate and distinct. While the blue color indicates discrete behavior, the green color indicates
continuous behavior. On one hand, the discrete view defines the headers and can be easily sorted, while continuous defines the axis in a graph view and cannot be sorted. Image - tableau.com Aggregation of data means displaying the measures and dimensions in an aggregated form. The aggregate functions available in the Tableau tool are: Tableau, in fact, lets you alter the aggregation type for a view. Disaggregation of data means displaying each and every data field separately. Tableau is pretty similar to SQL. Therefore, the types of joins in Tableau are similar: Learn More There are two types of data connections in Tableau:1. What is data visualization in Tableau?
2. What is the difference between various BI tools and Tableau?
3. What are different Tableau products?
4. What is a parameter in Tableau?
5. Tell me something about measures and dimensions?
6. What are continuous and discrete field types?
7. What is aggregation and disaggregation of data?
8. What are the different types of joins in Tableau?
9. Tell me the different connections to make with a dataset?
LIVE: Live connection is a dynamic way to extract real-time data by directly connecting to the data source. Tableau directly creates queries against the database entries and retrieves the query results in a workbook.
EXTRACT: A snapshot of the data, extract the file (.tde or .hyper file) contains data from a relational database. The data is extracted from a static source of data like an Excel Spreadsheet. You can schedule to refresh the snapshots which are done using the Tableau server. This doesn’t need any connection with the database.
10. What are the supported file extensions in Tableau?
The supported file extensions used in Tableau Desktop are:
- Tableau Workbook (TWB): contains all worksheets, story points, dashboards, etc.
- Tableau Data Source (TDS): contains connection information and metadata about your data source
- Tableau Data Extract (TDE): contains data that has been extracted from other data sources.
- Tableau Packaged Workbook (TWBX): contains a combination of the workbook, connection data, and metadata, and the data itself in the form of TDE. It can be zipped and shared.
- Tableau Packaged Data Source (TDSX): contains a combination of different files.
- Tableau Bookmark (TBM): to earmark a specific worksheet.
11. What are the supported data types in Tableau?
The following data types are supported in Tableau:
Boolean | True/False |
Date | Date Value (December 28, 2016) |
Date & Time | Date & Timestamp values (December 28, 2016 06:00:00 PM) |
Geographical Values | Geographical Mapping (Beijing, Mumbai) |
Text/String | Text/String |
Number | Decimal (8.00) |
Number | Whole Number (5) |
12. What are sets?
Sets are custom fields created as a subset of the data in your Tableau desktop. Sets can be computed based on conditions or created manually based on the dimensions of the data source.
For example, A set of customers that earned revenue more than some value. Now, set data may update dynamically based on the conditions applied.
Learn More
13. What are groups in Tableau?
Groups are created to visualize larger memberships using dimensions. Groups can create their own fields to categorize values in that specific dimension.
14. What are shelves?
Tableau worksheets contain various named elements like columns, rows, marks, filters, pages, etc. which are called shelves. You can place fields on shelves to create visualizations, increase the level of detail, or add context to it.
15. Tell me something about Data blending in Tableau?
Data blending is viewing and analyzing data from multiple sources in one place. Primary and secondary are two types of data sources that are involved in data blending.
16. How do you generally perform load testing in Tableau?
Load testing in Tableau is done to understand the server’s capacity with respect to its environment, data, workload, and use. It is preferable to conduct load testing at least 3-4 times in a year because with every new user, upgrade, or content authoring, the usage, data, and workload change.
Tabjolt was created by Tableau to conduct point-and-run load and performance testing specifically for Tableau servers. Tabjolt:
- Automates the process of user-specified loads
- Eliminates dependency on script development or script maintenance
- Scales linearly with an increase in the load by adding more nodes to the cluster
17. Why would someone not use Tableau?
The limitations of using Tableau are:
- Not cost-effective: Tableau is not that cost-effective when we compare it well with the other available data visualization tools. In addition to this, it has software upgrades, proper deployment, maintenance, and also training people for using the tool.
- Not so secure: When it comes to data, everyone is extra cautious. Tableau focussed on security issues but fails to provide centralized data-level security. It pushes for row-level security and creates an account for every user which makes it more prone to security glitches.
- BI capabilities are not enough: Tableau lacks basic BI capabilities like large-scale reporting, building data tables, or creating static layouts. It has limited result-sharing capabilities, email notification configuration is limited to admins, and the vendor doesn’t support trigger-based notifications.
Tableau Interview Questions For Experienced
27. How do you embed views into webpages?
You can easily integrate interactive views from your Tableau Server or Tableau online onto webpages, blogs, web applications, or internet portals. But to have a look at the views, the permissions demand the viewer to create an account on the Tableau Server. To embed views, click the Share button on the top of the view and copy the embed code to paste it on the web page.
You can also customize the embedded code or Tableau Javascript APIs to embed views.
28. What is the maximum no. of rows Tableau can utilize at one time?
The maximum number of rows or columns is indefinite because even though Tableau contains petabytes of data, it intelligently uses only those rows and columns which you need to extract for your purpose.
29. Mention what is the difference between published data sources and embedded data sources in Tableau?
Connection information is the details of data that you want to bring into Tableau. Before publishing it, you can create an extract of the same.
Published Data Source: It contains connection information that is independent of any workbook.
Embedded Data Source: It contains connection information which is connected to a workbook
30. What is the DRIVE Program Methodology?
DRIVE program methodology creates a structure around data analytics derived from enterprise deployments. The drive methodology is iterative in nature and includes agile methods that are faster and effective.
31. How to use groups in a calculated field?
Add the ‘GroupBy’ clause to SQL queries or create a calculated field in the data window to group fields.
- Using groups in a calculation. You cannot reference ad-hoc groups in a calculation.
- Blend data using groups created in the secondary data source: Only calculated groups can be used in data blending if the group was created in the secondary data source.
- Use a group in another workbook. You can easily replicate a group in another workbook by copy and pasting a calculation.
32. Explain when would you use Joins vs. Blending in Tableau?
While the two terms may sound similar, there is a difference in their meaning and use in Tableau:
While Join is used to combine two or more tables within the same data source.
Blending is used to combine data from multiple data sources such as Oracle, Excel, SQL server, etc.
33. What is Assume referential integrity?
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.
34. What is a Calculated Field, and How Will You Create One?
Calculated fields are created using formulas based on other fields. These fields do not exist but are created by you.
You can create these fields to:
- Segment data
- Convert the data type of a field, such as converting a string to a date.
- Aggregate data
- Filter results
- Calculate ratios
There are three main types of calculations that you can create:
- Basic Calculations: Transform values of the data fields at the source level
- Level of Detail (LOD) Expressions: Transform values of the data fields at the source level like basic calculations but with more granular access
- Table Calculations: Transform values of the data fields only at the visualization level
To create calculate fields:
In Tableau, navigate to Analysis>Create a calculated field. Input details in the calculation editor.
And, done!
35. How Can You Display the Top Five and Bottom Five Sales in the Same View?
You can see top five and bottom five sales with the help of these functions:
- Drag ‘customer name’ to row and sales to the column.
- Sort Sum(sales) in descending order.
- Create a calculated field ‘Rank of Sales’.
36. What is the Rank Function in Tableau?
Rank function is used to give positions (rank) to any measure in the data set. Tableau can rank measure in the following ways:
- Rank: The rank function in Tableau accepts two arguments: aggregated measure and ranking order (optional) with a default value of desc.
- Rank_dense: The rank_dense also accepts the two arguments: aggregated measure and ranking order. This assigns the same rank to the same values but doesn’t stop there and keeps incrementing with the other values. For instance, if you have values 10, 20, 20, 30, then ranks will be 1, 2, 2, 3.
- Rank_modified: The rank_modified assigns the same rank to similar values.
- Rank_unique: The rank_unique assigns a unique rank to each and every value. For example, If the values are 10, 20, 20, 30 then the assigned ranks will be 1,2,3,4 respectively.
37. What is the difference between Tableau and other similar tools like QlikView or IBM Cognos?
Tableau is different than QlikView or IBM Cognos for various reasons:
- Tableau is an intuitive data visualization tool simplifying the story creation by simple drag and drop techniques. On the other hand, BI tools like QlikView or Cognos convert data into metadata to let the users explore data relations. If your presentation runs around presenting data in aesthetic visualizations then opt for Tableau. If not, and might need a full BI platform then go for Cognos/QlikView
- The ease of use or extracting data details is easier in Tableau than compared to extensive BI tools like Cognos. With Tableau, your team members, be it a guy from sales can easily read the data and give insights. But with Cognos, only members with extensive tool knowledge are appreciated and welcomed.
Tips to clear an interview
To clear interview for Tableau, follow these tips:
- Focus on the fundamentals: What is Tableau and its working. How calculations work or how a query is processed when visualization is created.
- Thoroughly know about Dimensions and Measures because that is one of the important concepts in Tableau.
- Get acquainted with the best practices of creating dashboards and visualizations and also discrete and continuous views.
- Explain why you like Tableau or how it differs from other similar tools like QlikView or IBM Cognos. Your interest in BI tools will put you ahead in the competition.
- What are the scenarios where you’ll use Live connection or Data extract in Tableau?
- How dashboards are deployed on the Server.
- What was the maximum amount of data you have handled in Tableau? If you are learning Tableau, while practicing, check the size of your visualization or the TDE file.
- Create some visualization stories for sample work.
- How you will take requirements before creating a dashboarding application.
- What was your development methodology: Waterfall or Agile?
- How much time it takes you to create a dashboard.
Important Resource
Tableau vs Power BI
Tableau MCQs
It is identified by a blue pill in the visualization.
It is identified by a green pill in a visualization.
It is preceded by a # symbol in the data window.
When added to the visualization, it produces distinct values.
Sets
Groups
Calculated fields
Table Calculations
Bar
Line
Histogram
Scatter Plots
California
Colorado
Montana
New Mexico
Analyzing the trend for a time period
Comparing the actual against the target sales
Adding data to bins and calculating count measure
Displaying the sales growth for a particular year
Sets
Gatherings
Computed Fields
Table Estimations
The context filter isn’t oft-times modified by the user – if the filter is modified the info should recompute and rewrite the temporary table, deceleration performance.
When you set a dimension to context, Tableau creates a brief table that will need a reload when the read is initiated
Both A and B