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Limitless Analytics with Azure Synapse

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

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Product type Paperback
Published in Jun 2021
Publisher Packt
ISBN-13 9781800205659
Length 392 pages
Edition 1st Edition
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Authors (2):
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Saranya Ravichander Saranya Ravichander
Author Profile Icon Saranya Ravichander
Saranya Ravichander
Prashant Kumar Mishra Prashant Kumar Mishra
Author Profile Icon Prashant Kumar Mishra
Prashant Kumar Mishra
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Toc

Table of Contents (20) Chapters Close

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!

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