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


This chapter concludes the entire book. In this chapter, we learned about implementing the best practices for Synapse SQL pools and Spark pools. We learned how we keep indexes healthy in a SQL pool such that we gain better performance, and we also learned about using PolyBase and materialized views in Synapse dedicated SQL pools for enhanced performance. This chapter also included the best file type and size to be used in the case of a Synapse serverless SQL pool. Configuring the Auto pause setting to help save costs in terms of computational power was also highlighted in this chapter. Last but not least, we learned about memory considerations and bucketing in a Spark pool.

I am thankful to you for traveling with me on this learning journey. Congratulations on reaching the finish line in this book, and I wish you all the best as you continue exploring Azure Synapse.

Hope to meet you again in my next learning journey!