You're reading from Microsoft Power BI Performance Best Practices Learn practical techniques for building high-speed Power BI solutions

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781835082256

Length 346 pages

Edition 2nd Edition

Languages

DAX

Tools

Azure

Concepts

Business Intelligence

Authors (2):

Thomas LeBlanc

Bhavik Merchant

View More author details

Table of Contents (23) Chapters

Preface

1. Part 1: Architecture, Bottlenecks, and Performance Targets FREE CHAPTER

2. Chapter 1: Setting Targets and Identifying Problem Areas

3. Chapter 2: Exploring Power BI Architecture and Configuration

4. Chapter 3: Learning the Tools for Performance Tuning

5. Part 2: Performance Analysis, Improvement, and Management

6. Chapter 4: Analyzing Logs and Metrics

7. Chapter 5: Optimization for Storage Modes

8. Chapter 6: Third-Party Utilities

9. Chapter 7: Performance Governance Framework

10. Part 3: Fetching, Transforming, and Visualizing Data

11. Chapter 8: Loading, Transforming, and Refreshing Data

12. Chapter 9: Report and Dashboard Design

13. Part 4: Data Models, Calculations, and Large Semantic Models

14. Chapter 10: Dimensional Modeling and Row Level Security

15. Chapter 11: Improving DAX

16. Chapter 12: High Scale Patterns

17. Part 5: Optimizing Capacities in Power BI Enterprises

18. Chapter 13: Working with Capacities

19. Chapter 14: Performance Needs for Fabric Artifacts

20. Chapter 15: Embedding in Web Apps

21. Index

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Performance Needs for Fabric Artifacts

In the previous chapter, we looked at how to manage and monitor capacities. In this chapter, we will look specifically at the new artifacts in Fabric capacities that were not in Premium capacities. Fabric was created by Microsoft to simplify the modern data warehouse. All artifacts created are constructed to either relieve you of managing infrastructure or improve the performance of data warehouse development.

This chapter will give an overview of OneLake, Fabric’s data storage, which is like OneDrive for data. The warehouse or lakehouse gives a container for tables or files plus coding areas. Inside each container is a default semantic model for Power BI to report the data. Alerts have been integrated into the streaming resource to help with real-time requirements. Data science people will have OneLake to consume raw, curated, or dimensional data.

The whole point of Fabric is to improve performance by consolidating common data warehouse...