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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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Toc

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

Chapter 13: Performing Advanced Analysis

We have already covered how, as a report author, you can use features to enhance your reports for analytical insights, such as Q&A and exporting. In this chapter, you will closely examine your data and Power BI reports and then extract value with deeper analysis. You will learn how to get a statistical summary for your data, analyze time series data, and group and bin your data. You will also apply and perform advanced analytics on the report for deeper and more meaningful data insights.

In this chapter, we will cover the following:

  • Identifying outliers
  • Using anomaly detection
  • Conducting time series analysis
  • Using grouping and binning
  • Using the key influencers to explore dimensional variances
  • Using the decomposition tree visual to break down a measure
  • Applying AI insights

These are some of the more advanced features of Power BI. They allow you to become your own junior data scientist, granting you...

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