20 Tableau CRM Interview Questions and Answers

Tableau CRM is a powerful customer relationship management software that helps businesses manage their customer data. If you’re interviewing for a position that involves working with Tableau CRM, it’s important to be prepared to answer questions about the software. In this article, we’ll review some of the most common Tableau CRM interview questions and provide tips on how to answer them.

Tableau CRM Interview Questions and Answers

Here are 20 commonly asked Tableau CRM interview questions and answers to prepare you for your interview:

1. What is Tableau CRM?

Tableau CRM is a software application that helps businesses manage their customer relationships. It provides a number of features and tools to help businesses track and manage customer data, including contact information, customer interactions, and sales data. Tableau CRM can also help businesses create and manage customer loyalty programs, and track customer satisfaction levels.

2. Do you think it’s a good idea to use Tableau for data visualization? Why or why not?

I think that Tableau is a great tool for data visualization for a few reasons. First, it is very user-friendly and easy to learn, even for those who are not familiar with data visualization tools. Second, it has a lot of features and options that allow you to customize your visualizations to fit your specific needs. Finally, it integrates well with other data sources and tools, which makes it a great option for those who need to work with data from multiple sources.

3. How can I use Tableau on my Macbook?

Tableau is a business intelligence software that can be used to visualize data. Tableau can be used on a Macbook by downloading the Tableau Desktop application from the Tableau website.

4. Can you explain the difference between “data blending” and “joining”?

When you “join” data in Tableau, you are essentially combining two data sources into one. This is typically done by matching up fields in each data source that contain the same data. For example, you might join a customer list with a sales list by matching up customer IDs.

“Data blending” is a bit different in that it allows you to combine data from two data sources, even if there are no matching fields between them. This is done by creating a “link” between the two data sources. Tableau will then use this link to blend the data from the two sources together.

5. When would you recommend using Tableau Desktop as opposed to Tableau Public?

Tableau Desktop is the more powerful of the two options, and is recommended for users who need more flexibility and control over their data visualizations. Tableau Public is more limited, but is a good option for users who do not need as many features and who want to be able to share their visualizations more easily.

6. Can you explain what predictive analytics means in the context of Customer Relationship Management?

Predictive analytics is the process of using data and statistical models to make predictions about future events. In the context of CRM, predictive analytics can be used to identify patterns in customer behavior in order to better target marketing efforts, improve customer service, and make other decisions that will help to improve the overall relationship between a company and its customers.

7. Is there any way to install Tableau without administrator privileges? If yes, then how?

Yes, it is possible to install Tableau without administrator privileges. However, you will need to have access to the Tableau installation files in order to do so. Once you have those files, you can simply run the Tableau installer and follow the prompts.

8. Can you explain what an OLAP cube is?

An OLAP cube is a data structure that allows for efficient querying and analysis of data. OLAP cubes are often used in business intelligence and data warehousing applications.

9. Which types of charts are supported by Tableau?

Tableau supports a variety of charts, including bar charts, line charts, pie charts, and scatter plots.

10. Can you explain the purpose of having both Tableau Desktop and Tableau Server?

Tableau Desktop is used for authoring and designing visualizations, while Tableau Server is used for sharing those visualizations with other users. Tableau Server provides a web-based interface for interacting with Tableau visualizations, as well as a number of other features such as security and administration.

11. What do you understand about collaborative filtering?

Collaborative filtering is a method of making recommendations based on the collective input of a group of people. In the context of a CRM system, it could be used to suggest potential customers to a salesperson based on the collective input of the sales team.

12. What are some examples of business intelligence tools that can be used with Tableau?

Some examples of business intelligence tools that can be used with Tableau are Microsoft Power BI, IBM Watson, and Google Analytics.

13. Why do you think Tableau is gaining popularity over other Business Intelligence solutions like Cognos and Business Objects?

I think there are a few reasons. First, Tableau is much easier to use and doesn’t require as much training as the other options. Second, Tableau is much more flexible and can be used for a wider variety of tasks. And finally, Tableau is much cheaper than the other options, which makes it more accessible to small and medium businesses.

14. What is your understanding of dashboard actions in Tableau?

Dashboard actions are a way to create interactive dashboards in Tableau. By using dashboard actions, you can create links between different views in your dashboard, allowing your users to drill down into the data to see more detailed information. You can also use dashboard actions to filter data, highlight data, and even open up new windows with additional information.

15. Give me a real-world example where you have successfully used Tableau to solve a problem?

I was working with a client who was trying to track customer satisfaction rates. We used Tableau to create a dashboard that showed customer satisfaction rates over time. This allowed us to quickly see which areas we needed to improve in and where we were doing well.

16. In your experience, what type of datasets tend to work best with Tableau?

In my experience, Tableau works best with datasets that are well organized and have a clear structure. Additionally, Tableau is particularly good at visualizing data that has a spatial element to it. For example, data that includes geographical information or data that includes a lot of points or data that can be plotted on a map.

17. What are some limitations of Tableau?

One potential limitation of Tableau is that it can be difficult to scale up. As your data sets grow larger and more complex, Tableau can start to slow down. Additionally, Tableau is not as robust when it comes to predictive analytics and modeling as some other data visualization tools.

18. What are some ways to increase adoption of Tableau within an organization?

There are a few different ways that you can increase adoption of Tableau within an organization. One way is to make sure that you are providing training and support to users so that they feel comfortable using the software. Another way is to make sure that you are integrating Tableau into existing workflows and processes so that users can see the value that it can add. Finally, you can also try to create a community of Tableau users so that people can share tips, tricks, and best practices.

19. What is your opinion on the security features provided by Tableau?

I believe that the security features provided by Tableau are adequate for most purposes. However, if you are working with sensitive data, you may want to consider using a more robust security solution.

20. What are some challenges you’ve faced while working with Tableau?

One challenge I’ve faced is that Tableau can be very resource-intensive, so it’s important to make sure that your computer can handle it before you start using it. Another challenge is that Tableau can be difficult to learn if you don’t have any previous experience with data visualization software.