Book Image

Limitless Analytics with Azure Synapse

By : Prashant Kumar Mishra
Book Image

Limitless Analytics with Azure Synapse

By: Prashant Kumar Mishra

Overview of this book

Azure Synapse Analytics, which Microsoft describes as the next evolution of Azure SQL Data Warehouse, is a limitless analytics service that brings enterprise data warehousing and big data analytics together. With this book, you'll learn how to discover insights from your data effectively using this platform. The book starts with an overview of Azure Synapse Analytics, its architecture, and how it can be used to improve business intelligence and machine learning capabilities. Next, you'll go on to choose and set up the correct environment for your business problem. You'll also learn a variety of ways to ingest data from various sources and orchestrate the data using transformation techniques offered by Azure Synapse. Later, you'll explore how to handle both relational and non-relational data using the SQL language. As you progress, you'll perform real-time streaming and execute data analysis operations on your data using various languages, before going on to apply ML techniques to derive accurate and granular insights from data. Finally, you'll discover how to protect sensitive data in real time by using security and privacy features. By the end of this Azure book, you'll be able to build end-to-end analytics solutions while focusing on data prep, data management, data warehousing, and AI tasks.
Table of Contents (20 chapters)
Section 1: The Basics and Key Concepts
Section 2: Data Ingestion and Orchestration
Section 3: Azure Synapse for Data Scientists and Business Analysts
Section 4: Best Practices


In this chapter, we covered Azure Synapse Link, which is a new feature added to Azure Synapse, and we learned a step-by-step process to query data directly from an Azure Cosmos DB account. This feature dispenses with the need for ETL processes to bring data from a Cosmos DB account to Synapse. Now, we know that we can write queries directly on Cosmos DB data by creating corresponding linked services. We also saw how the transactional store syncs the data in the analytical store through auto-sync, and we learned about modes of schema representation in the analytical store. We used the Python language in this chapter; however, you are free to use any supported language that you are comfortable with.

There are many possible use cases of Azure Synapse Link. You can find a couple of these use cases mentioned in Microsoft Docs:

In the next chapter, we are going to get some good coding experience on Azure...