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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

In this chapter, we learned how to create a linked service for machine learning in Azure Synapse and how to use a key vault to store secrets for cognitive services. We also learned how to use Azure ML with Azure Synapse in order to use new or existing ML models to enrich our data. We then learned how can we use Cognitive Services directly on our data without writing even a single line of code. There are various steps involved before we can start using Cognitive Services on our data and we went through all these technical requirements. Sample notebooks were also provided to understand the approach to using Spark AutoML and Spark MLlib on the data.

With this chapter, we've covered and understood all the concepts of Azure Synapse. In the next chapter, we will learn different ways to perform backup and restore operations in Azure Synapse.

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