You're reading from Limitless Analytics with Azure Synapse An end-to-end analytics service for data processing, management, and ingestion for BI and ML

Product type Paperback

Published in Jun 2021

Publisher Packt

ISBN-13 9781800205659

Length 392 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Data Processing

Authors (2):

Saranya Ravichander

Prashant Kumar Mishra

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Table of Contents (20) Chapters

Preface

1. Section 1: The Basics and Key Concepts

2. Chapter 1: Introduction to Azure Synapse FREE CHAPTER

3. Chapter 2: Considerations for Your Compute Environment

4. Section 2: Data Ingestion and Orchestration

5. Chapter 3: Bringing Your Data to Azure Synapse

6. Chapter 4: Using Synapse Pipelines to Orchestrate Your Data

7. Chapter 5: Using Synapse Link with Azure Cosmos DB

8. Section 3: Azure Synapse for Data Scientists and Business Analysts

9. Chapter 6: Working with T-SQL in Azure Synapse

10. Chapter 7: Working with R, Python, Scala, .NET, and Spark SQL in Azure Synapse

11. Chapter 8: Integrating a Power BI Workspace with Azure Synapse

12. Chapter 9: Perform Real-Time Analytics on Streaming Data

13. Chapter 10: Generate Powerful Insights on Azure Synapse Using Azure ML

14. Section 4: Best Practices

15. Chapter 11: Performing Backup and Restore in Azure Synapse Analytics

16. Chapter 12: Securing Data on Azure Synapse

17. Chapter 13: Managing and Monitoring Synapse Workloads

18. Chapter 14: Coding Best Practices

19. Other Books You May Enjoy

Summary

This chapter concludes the entire book. In this chapter, we learned about implementing the best practices for Synapse SQL pools and Spark pools. We learned how we keep indexes healthy in a SQL pool such that we gain better performance, and we also learned about using PolyBase and materialized views in Synapse dedicated SQL pools for enhanced performance. This chapter also included the best file type and size to be used in the case of a Synapse serverless SQL pool. Configuring the Auto pause setting to help save costs in terms of computational power was also highlighted in this chapter. Last but not least, we learned about memory considerations and bucketing in a Spark pool.

I am thankful to you for traveling with me on this learning journey. Congratulations on reaching the finish line in this book, and I wish you all the best as you continue exploring Azure Synapse.

Hope to meet you again in my next learning journey!