Limitless Analytics with Azure Synapse

An end-to-end analytics service for data processing, management, and ingestion for BI and ML requirements

Prashant Kumar Mishra 지음

Packt(GCO Science) 2021년 06월 18일 출간

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Leverage the Azure analytics platform's key analytics services to deliver unmatched intelligence for your data

▶Book Description
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.

▶What You Will Learn
-Explore the necessary considerations for data ingestion and orchestration while building analytical pipelines
-Understand pipelines and activities in Synapse pipelines and use them to construct end-to-end data-driven workflows
-Query data using various coding languages on Azure Synapse
-Focus on Synapse SQL and Synapse Spark
-Manage and monitor resource utilization and query activity in Azure Synapse
-Connect Power BI workspaces with Azure Synapse and create or modify reports directly from Synapse Studio
-Create and manage

목차

▶TABLE of CONTENTS
▷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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▶What this book covers
- Chapter 1, Introduction to Azure Synapse, provides an overview of all the components that make up the Synapse workspace: dedicated SQL pool, Spark pools, Synapse pipelines, Azure Machine Learning, and Power BI. In this chapter, you will learn the basics of Synapse and how to create your first Synapse workspace.

- Chapter 2, Considerations for Your Compute Environment, focuses on the compute environments of Synapse. This chapter will focus mainly on dedicated SQL pool, serverless SQL pools, and Spark pools. It will help you choose the correct environment for your business problem.

- Chapter 3, Bringing Your Data to Azure Synapse, covers multiple options to bring your data from various sources to Azure Synapse. You will learn how to use different services to set up a connection with Azure Synapse.

- Chapter 4, Using Synapse Pipelines to Orchestrate Your Data, focuses on Synapse pipelines, which are very similar to Azure Data Factory pipelines; however, you don't need to create a separate Data Factory pipeline for orchestration. Instead, you can perform all the operations you need to do directly within Synapse Studio.

- Chapter 5, Using Synapse Link with Azure Cosmos DB, is where you will learn how you can perform analytics operations directly on Cosmos DB data without moving data. This chapter will help you understand how Synapse Link has reduced the total time required for running an analytics operation on Cosmos DB data by removing the need for data movement from Cosmos DB to Azure Synapse.

- Chapter 6, Working with T-SQL in Azure Synapse, teaches you how to query data using T-SQL on Azure Synapse. This chapter will cover the pre-requisites and provide the details for sample data that can be used to perform some simple operations on Azure Synapse using T-SQL.

- Chapter 7, Working with R, Python, Scala, .NET, and Spark SQL in Azure Synapse, covers how to query data using various coding languages on Azure Synapse. This chapter will cover

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▶ Preface
Azure Synapse Analytics is an analytics platform offered by the Microsoft Azure cloud platform. This book will help you understand the basic concepts of Azure Synapse and get you familiar with how it works in practice, step by step. This book has been written in simple language and with plenty of diagrams to make it easier for you to understand the concepts.

Each main topic has a whole chapter dedicated to it, such that even the minor concepts are explained in detail. You just need to have a basic knowledge of SQL Data Warehouse and Azure generally to follow the topics in this book.

To fully understand Azure Synapse, you need to understand a few other technologies as well, such as Power BI, Azure Data Factory, and Azure Machine Learning. I have tried to cover these services and how they are integrated together with Azure Synapse. Overall, this book should leave anyone well equipped to start working on Azure's analytics platform within a week.

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저자(글) Prashant Kumar Mishra

Prashant Kumar Mishra is an engineering architect at Microsoft. He has more than 10 years of professional expertise in the Microsoft data and AI segment as a developer, consultant, and architect. He has been focused on Microsoft Azure Cloud technologies for several years now and has helped various customers in their data journey. He prefers to share his knowledge with others to make the data community stronger day by day through his blogs and meetup groups.