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

Product type Paperback

Published in Jun 2022

Publisher Packt

ISBN-13 9781803238562

Length 398 pages

Edition 1st Edition

Languages

DAX

Tools

Power BI

Concepts

IT Certification

Authors (2):

Edward Corcoran

Orrin Edenfield

View More author details

Table of Contents (25) Chapters

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

Using anomaly detection

One of the great ways to find outliers is using the built-in Find anomalies tool in the Analysis pane of a visualization in Power BI. This feature of Power BI uses Artificial Intelligence (AI) capabilities to identify which data points are most different from other values in your data. The purpose of this feature is to help with analyzing the data so that action can be taken either against the data before business decisions are made or to help report consumers better understand the data and make informed business decisions.

To use this capability, you need to be using a supported visual (such as a line or scatter chart) and only one field on the y axis or values. This feature is being improved; so, at the time of writing, this was the requirement.

Figure 13.2 – Automated anomaly detection is built into some visualizations

Once this has been enabled, you can see the outliers identified with a gray dot. These are anomalies that...