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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

Define the tables

As mentioned in the introduction, once you've acquired your data, cleaned it, and organized it, you can start to model it. Usually, a simpler model will perform better than a complicated model. As every situation is different, there are a few hard-and-fast rules for simplifying your data model. This is good news for you, as you will encounter a few questions about this and most are common sense.

When creating tables, what you leave out can be as important as what you keep. Typically, if a column or table is not necessary for a visual or a calculation, do not include it in the model. If you bring in more tables and columns than you need, not only will the reports based on the model be slower but it can also lead to confusion. If you import all the tables from your database, report creators will have to search through all the tables to find the columns they need to report on. This can lead to frustration, especially if the end result is a slow-running report...

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