What this book covers
Chapter 1, Introduction to Azure Synapse, provides an overview of all the components that make up the Synapse workspace: dedicated SQL pool, Spark pools, Synapse pipelines, Azure Machine Learning, and Power BI. In this chapter, you will learn the basics of Synapse and how to create your first Synapse workspace.
Chapter 2, Considerations for Your Compute Environment, focuses on the compute environments of Synapse. This chapter will focus mainly on dedicated SQL pool, serverless SQL pools, and Spark pools. It will help you choose the correct environment for your business problem.
Chapter 3, Bringing Your Data to Azure Synapse, covers multiple options to bring your data from various sources to Azure Synapse. You will learn how to use different services to set up a connection with Azure Synapse.
Chapter 4, Using Synapse Pipelines to Orchestrate Your Data, focuses on Synapse pipelines, which are very similar to Azure Data Factory pipelines; however, you don't need to create a separate Data Factory pipeline for orchestration. Instead, you can perform all the operations you need to do directly within Synapse Studio.
Chapter 5, Using Synapse Link with Azure Cosmos DB, is where you will learn how you can perform analytics operations directly on Cosmos DB data without moving data. This chapter will help you understand how Synapse Link has reduced the total time required for running an analytics operation on Cosmos DB data by removing the need for data movement from Cosmos DB to Azure Synapse.
Chapter 6, Working with T-SQL in Azure Synapse, teaches you how to query data using T-SQL on Azure Synapse. This chapter will cover the pre-requisites and provide the details for sample data that can be used to perform some simple operations on Azure Synapse using T-SQL.
Chapter 7, Working with R, Python, Scala, .NET, and Spark SQL in Azure Synapse, covers how to query data using various coding languages on Azure Synapse. This chapter will cover the pre-requisites and provide details on sample data that can be used to perform simple operations on Azure Synapse using R, Python, Scala, .NET, and Spark SQL.
Chapter 8, Integrating a Power BI Workspace with Azure Synapse, explores how to integrate a Power BI workspace with Azure Synapse and how you can connect Azure Synapse data to Power BI Desktop.
Chapter 9, Perform Real-Time Analytics on Streaming Data, looks at how to perform real-time analytics on streaming data. This chapter focuses on bringing streaming data to Synapse and performing operations on this data using various languages.
Chapter 10, Generate Powerful Insights on Azure Synapse Using Azure Machine Learning, shows you how to integrate Azure Machine Learning with Azure Synapse. You will also learn how to use different languages to pair Azure Machine Learning with Azure Synapse.
Chapter 11, Performing Backup and Restore in Azure Synapse Analytics, is where you will learn how to use backup and restore in Azure Synapse SQL pools. You will learn about automatic and user-defined restore points. This chapter covers how a user can perform cross-subscription restores and geo-redundant restores as well.
Chapter 12, Securing Data on Azure Synapse, talks about how to secure customer data on Azure Synapse. It is very important to understand how you can keep your data safe. This chapter guides you on how you can enable all the best security measures in your Synapse workspace.
Chapter 13, Managing and Monitoring Synapse Workloads, focuses on manageability and monitoring resource utilization and query activity in Azure Synapse Analytics.
Chapter 14, Coding Best Practices, helps you to understand the best practices for performance and management. In this chapter, you will also learn about the best practices for dedicated SQL pools, serverless SQL pools, and Spark pools.