
Limitless Analytics with Azure Synapse
By :

Limitless Analytics with Azure Synapse
By:
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)
Preface
Section 1: The Basics and Key Concepts
Chapter 1: Introduction to Azure Synapse
Chapter 2: Considerations for Your Compute Environment
Section 2: Data Ingestion and Orchestration
Chapter 3: Bringing Your Data to Azure Synapse
Chapter 4: Using Synapse Pipelines to Orchestrate Your Data
Chapter 5: Using Synapse Link with Azure Cosmos DB
Section 3: Azure Synapse for Data Scientists and Business Analysts
Chapter 6: Working with T-SQL in Azure Synapse
Chapter 7: Working with R, Python, Scala, .NET, and Spark SQL in Azure Synapse
Chapter 8: Integrating a Power BI Workspace with Azure Synapse
Chapter 9: Perform Real-Time Analytics on Streaming Data
Chapter 10: Generate Powerful Insights on Azure Synapse Using Azure ML
Section 4: Best Practices
Chapter 11: Performing Backup and Restore in Azure Synapse Analytics
Chapter 12: Securing Data on Azure Synapse
Chapter 13: Managing and Monitoring Synapse Workloads
Chapter 14: Coding Best Practices
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