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

View More author details

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

Technical requirements

Before you start orchestrating your data, here are certain prerequisites that you should meet:

You should have an Azure subscription, or access to any other subscription with contributor-level access.
Create your Synapse workspace on this subscription. You can follow the instructions from Chapter 1, Introduction to Azure Synapse, to create your Synapse workspace.
Create a SQL pool on Azure Synapse. This has been covered in Chapter 2, Considerations For Your Compute Environment.
Download the script from the following link: http://bit.ly/T-SQL-samples.

Once you have met all the prerequisites, you can start transforming your business logic into code by using T-SQL. In the following section, we will learn about some of the supported features by using some sample queries.