Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Tableau 2023

You're reading from   Mastering Tableau 2023 Implement advanced business intelligence techniques, analytics, and machine learning models with Tableau

Arrow left icon
Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781803233765
Length 684 pages
Edition 4th Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Marleen Meier Marleen Meier
Author Profile Icon Marleen Meier
Marleen Meier
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Reviewing the Basics 2. Getting Your Data Ready FREE CHAPTER 3. Using Tableau Prep Builder 4. Learning about Joins, Blends, and Data Structures 5. Introducing Table Calculations 6. Utilizing OData, Data Densification, Big Data, and Google BigQuery 7. Practicing Level of Detail Calculations 8. Going Beyond the Basics 9. Working with Maps 10. Presenting with Tableau 11. Designing Dashboards and Best Practices for Visualizations 12. Leveraging Advanced Analytics 13. Improving Performance 14. Exploring Tableau Server and Tableau Cloud 15. Integrating Programming Languages 16. Developing Data Governance Practices 17. Other Books You May Enjoy
18. Index

Summary

We began this chapter with a discussion of the performance-recording dashboard. This was important because many of the subsequent exercises utilized the performance-recording dashboard to examine underlying queries. Next, we discussed hardware and on-the-fly techniques, where the intent was to communicate hardware considerations for good Tableau performance and, in the absence of optimal hardware, techniques for squeezing the best possible performance out of any computer.

Then we covered working with data sources, including joining, blending, and efficiently working with data sources. This was followed by a discussion on generating and using extracts as efficiently as possible. By focusing on data sources for these three sections, we learned best practices and what to avoid when working with either remote datasets or extracts. The next sections explored performance implications for various types of filters and calculations. Lastly, we looked at additional performance considerations...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime