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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 was primarily focused on Synapse SQL. We learned different T-SQL language elements that are supported in Synapse SQL, as well as their limitations. We learned how we can use T-SQL statements with structured, semi-structured, or unstructured data. In this chapter, we also covered how to manage transactions efficiently to avoid any transaction failures. We also learned that we could create stored procedures and views in Synapse SQL in a similar way to how we do this in SQL Server. Synapse SQL provides a few additional features to read data directly from a data lake.

We saw some of the system views supported in Synapse SQL. We also learned how to use sample scripts to build our logic as per the business need.

The next chapter will be more focused on Synapse Spark, where we will learn how to write code in different languages in Synapse Spark without worrying about infrastructure management. We will also learn how to use notebooks in Synapse Studio.

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