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

Creating an Azure ML linked service in Azure Synapse

Azure ML is a cloud-based service that can be used to create and manage machine learning solutions. You can easily link an Azure Synapse Analytics workspace with an Azure Machine Learning workspace in order to leverage various ML features within Azure Synapse. With this linked service created within your Azure Synapse workspace, you can directly bring a machine learning model from the Azure ML model registry and score the model in the Synapse SQL pool.

Most importantly, you can run your Azure Machine Learning pipelines directly from Azure Synapse by creating a Synapse pipeline and linking it to the ML linked service created in Azure Synapse. We will go through the required steps in this section.

For now, we will be creating an ML linked service in Azure Synapse, but before we do that, we need to register an application on Azure Active Directory. So, go through the following steps to complete the pre-requisites for creating...