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Microsoft Power BI Data Analyst Certification Guide

You're reading from   Microsoft Power BI Data Analyst Certification Guide A comprehensive guide to becoming a confident and certified Power BI professional

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781803238562
Length 398 pages
Edition 1st Edition
Languages
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Authors (2):
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Edward Corcoran Edward Corcoran
Author Profile Icon Edward Corcoran
Edward Corcoran
Orrin Edenfield Orrin Edenfield
Author Profile Icon Orrin Edenfield
Orrin Edenfield
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Table of Contents (25) Chapters Close

Preface 1. Part 1 – Preparing the Data
2. Chapter 1: Overview of Power BI and the PL-300 Exam FREE CHAPTER 3. Chapter 2: Connecting to Data Sources 4. Chapter 3: Profiling the Data 5. Chapter 4: Cleansing, Transforming, and Shaping Data 6. Part 2 – Modeling the Data
7. Chapter 5: Designing a Data Model 8. Chapter 6: Using Data Model Advanced Features 9. Chapter 7: Creating Measures Using DAX 10. Chapter 8: Optimizing Model Performance 11. Part 3 – Visualizing the Data
12. Chapter 9: Creating Reports 13. Chapter 10: Creating Dashboards 14. Chapter 11: Enhancing Reports 15. Part 4 – Analyzing the Data
16. Chapter 12: Exposing Insights from Data 17. Chapter 13: Performing Advanced Analysis 18. Part 5 – Deploying and Maintaining Deliverables
19. Chapter 14: Managing Workspaces 20. Chapter 15: Managing Datasets 21. Part 6 – Practice Exams
22. Chapter 16: Practice Exams 23. Other Books You May Enjoy Appendix: Practice Question Answers

Flatten out a parent-child hierarchy

Where possible, you should strive for simpler models. When your report builders see fewer tables, they will be able to use the model more effectively. The simpler the model, the fewer problems you will have with it. We are not saying leave out important data, but we are saying, again, if it's not necessary, don't include it.

The most common way to do this is by using a star schema.

Star schema

A star schema organizes your data into fact and dimension tables. You can use dimension tables to filter the fact table. Dimension tables contain information that is repeated over and over again, for example, in the Sales table. If you think of a product dimension, it can hold all the information about a product, such as the name, color, SKU, size, and weight. Instead of repeating that information over and over, you can represent the product by an SKU number or even an integer in the Sales table. You can then filter the Sales table by selecting...

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