Tableau Interview Q&A: Tableau For Data Science Careers

Overview

Tableau Interview Questions To Maximize Your Chances Of Getting A Data Analytics Or Tableau Developer Or Analyst Job What you'll learn:

Learn how to explain what Tableau isLearn who the founders of Tableau areLearn how to describe the mission of the companyLearn how to explain what a treemap visualisation isLearn about Tableau Desktop and Tableau Server row and column limitationsLearn the difference between .twb and .twbx filesLearn how aggregation works in TableauLearn everything how context filters workLearn two practical applications of context filtersLearn how data source filters workLearn how blends work in TableauLearn how to append data to a Tableau extractLearn how to "Union All" data using a Custom SQL queryUnderstand the difference between measures and dimensionsUnderstand the difference between discrete and continuous variablesLearn how to create a blended axis and how to control it This course is designed for me to pass on as much knowledge about Tableau to you as I can. We will go through the most popular Tableau questions and I will reveal how I would go about answering each of these questions.

Moreover, there will be ample examples in this course and I will explain my answers in detail and actually show you how it all plays out in the software. The course is broken up into three sections based on the question types:

SimpleModerateDifficultAlso you can use the questions in this course to check your knowledge of Tableau - after I reveal the question, pause the video and try to answer the question.

Then check if your answer is the same as mine. This is a short, dynamic, and fun course!

Unlike my other courses you won't have to do any exercises. The lectures have a conversational format, so all you need to do is relax and enjoy how we delve into the diverse world of Tableau.

I look forward to seeing you inside! Kirill Disclaimer:

This course does not guarantee you getting a job or promotion.

This course is designed to pass my knowledge of Tableau onto you. Although I have put in substantial effort into preparing this course there may be some things that are incorrect.

Therefore, do not rely solely on these answers - these are nothing more than my opinions and experiences. Make sure to verify any information independently.

I will not accept any responsibility for consequences of you relying on the information provided in this course for job interviews, professional work, and any other purposes.

Syllabus

• Introduction to Tableau
Overview of Tableau Software
Importance of Tableau in Data Science
Setting Up Tableau: Installation and Interface
• Basic Tableau Skills
Connecting to Data Sources
Data Preparation and Cleaning in Tableau
Creating First Visualizations: Bar Charts, Line Charts, and Pie Charts
• Intermediate Tableau Techniques
Advanced Graphs: Scatter Plots, Heat Maps, and Tree Maps
Working with Dashboard and Story Points
Applying Filters and Sorting Data
• Advanced Data Visualization
Calculated Fields and Table Calculations
Using Parameters for Interactive Dashboards
Advanced Analytics: Forecasting and Trend Lines
• Tableau for Data Science Applications
Case Studies: Real-World Data Science Scenarios
Integrating Tableau with R and Python
Performing Predictive Analytics with Tableau
• Preparing for Tableau Interviews
Common Tableau Interview Questions and Answers
Hands-on Practice: Solving Real Interview Problems
Tips and Tricks for Effective Interview Presentation
• Conclusion and Next Steps
Reviewing Key Concepts
Further Resources and Continuing Education
Final Q&A and Feedback Session

Taught by

Kirill Eremenko, SuperDataScience Team and Ligency Team

Subjects

Data Science