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)
1
Section 1: The Basics and Key Concepts
4
Section 2: Data Ingestion and Orchestration
8
Section 3: Azure Synapse for Data Scientists and Business Analysts
14
Section 4: Best Practices

Summary

In this chapter, we learned how to create a linked service for machine learning in Azure Synapse and how to use a key vault to store secrets for cognitive services. We also learned how to use Azure ML with Azure Synapse in order to use new or existing ML models to enrich our data. We then learned how can we use Cognitive Services directly on our data without writing even a single line of code. There are various steps involved before we can start using Cognitive Services on our data and we went through all these technical requirements. Sample notebooks were also provided to understand the approach to using Spark AutoML and Spark MLlib on the data.

With this chapter, we've covered and understood all the concepts of Azure Synapse. In the next chapter, we will learn different ways to perform backup and restore operations in Azure Synapse.