ETL with Azure Cookbook

Practical recipes for building modern ETL solutions to load and transform data from any source

Christian Cote , Matija Lah , Madina Saitakhmetova 지음

Packt(GCO Science) 2020년 09월 30일 출간

작품소개

책소개

Explore the latest Azure ETL techniques both on-premises and in the cloud using Azure services such as SQL Server Integration Services (SSIS), Azure Data Factory, and Azure Databricks

▶Book Description
ETL is one of the most common and tedious procedures for moving and processing data from one database to another. With the help of this book, you will be able to speed up the process by designing effective ETL solutions using the Azure services available for handling and transforming any data to suit your requirements.

With this cookbook, you'll become well versed in all the features of SQL Server Integration Services (SSIS) to perform data migration and ETL tasks that integrate with Azure. You'll learn how to transform data in Azure and understand how legacy systems perform ETL on-premises using SSIS. Later chapters will get you up to speed with connecting and retrieving data from SQL Server 2019 Big Data Clusters, and even show you how to extend and customize the SSIS toolbox using custom-developed tasks and transforms. This ETL book also contains practical recipes for moving and transforming data with Azure services, such as Data Factory and Azure Databricks, and lets you explore various options for migrating SSIS packages to Azure. Toward the end, you'll find out how to profile data in the cloud and automate service creation with Business Intelligence Markup Language (BIML).

By the end of this book, you'll have developed the skills you need to create and automate ETL solutions on-premises as well as in Azure.

▶What You Will Learn
？Explore ETL and how it is different from ELT
？Move and transform various data sources with Azure ETL and ELT services
？Use SSIS 2019 with Azure HDInsight clusters
？Discover how to query SQL Server 2019 Big Data Clusters hosted in Azure
？Migrate SSIS solutions to Azure and solve key challenges associated with it
？Understand why data profiling is crucial and how to implement it in Azure Databricks
？Get to grips with BIML and learn how it applies to SSIS and Azure Data Factory solutions

▶Key Features
？Understand the key components of an ETL solution using Azure Integration Services
？Discover the common and not-so-common challenges faced while creating modern and scalable ETL solutions
？Program and extend your packages to develop efficient data integration and data transformation solutions

▶Who This Book Is For
This book is for data warehouse architects, ETL developers, or anyone who wants to build scalable ETL applications in Azure. Those looking to extend their existing on-premise ETL applications to use big data and a variety of Azure services or others interested in migrating existing on-premise solutions to the Azure cloud platform will also find the book useful. Familiarity with SQL Server services is necessary to get the most out of this book.

목차

▶TABLE of CONTENTS
？ Chapter 1: Getting Started with Azure and SSIS 2019
？ Chapter 2: Introducing ETL
？ Chapter 3: Creating and Using SQL Server 2019 Big Data Clusters
？ Chapter 4: Azure Data Integration
？ Chapter 5: Extending SSIS with Custom Tasks and Transformations
？ Chapter 6: Azure Data Factory
？ Chapter 7: Azure Databricks
？ Chapter 8: SSIS Migration Strategies
？ Chapter 9: Profiling data in Azure
？ Chapter 10: Manage SSIS and Azure Data Factory with Biml

책 속으로

▶What this book covers
？ Chapter 1, Getting Started with Azure and SSIS 2019, describes, in step-by-step fashion, how to set up SQL Server 2019 to deploy the features that are used throughout the book. It also covers how to set up an Azure subscription.

？ Chapter 2, Introducing ETL, explains why ETL is needed, where it comes from, and the differences between ETL and ELT.

？ Chapter 3, Creating and Using SQL Server 2019 Big Data Clusters, discusses how to create, deploy, connect to, and retrieve data from SQL Server 2019 Big Data Clusters.

？ Chapter 4, Azure Data Integration, talks about the Azure Feature Pack, which allows SSIS to integrate Azure data from blob storage and HDInsight clusters.

？ Chapter 5, Extending SSIS with Custom Tasks and Transformations, talks about extending and customizing the built-in toolset with custom-developed control flow tasks and data flow transformations.

？ Chapter 6, Azure Data Factory, talks about using Azure Data Factory to move and transform data in the cloud.

？ Chapter 7, Azure Databricks, talks about using Azure Databricks to transform data in the cloud.

？ Chapter 8, SSIS cloud Migration Strategies, talks about scaling out SSIS packages to Azure.

？ Chapter 9, Profiling data in Azure, contains various recipes that show you how to perform data profiling in Azure Databricks.

？ Chapter 10, Manage SSIS and Azure Data Factory with BIML, contains various recipes that demonstrate how to manage SSIS and Azure Data Factory with BIML using metadata.

출판사 서평

▶ Preface
Extract, Transform, Load (ETL) is one of the most common and tedious procedures for moving and processing data from one database to another. With the help of this book, you will be able to speed up the process by designing efficient ETL solutions using the Azure services available for handling and transforming any data to suit your requirements.

With this cookbook, you will become well versed in all the features of SQL Server Integration Services (SSIS) to perform data migration and ETL tasks that integrate with Azure. You will learn how to transform data in Azure and understand how legacy systems perform ETL on-premises using SSIS. Later chapters will get you up to speed with connecting and retrieving data from SQL Server 2019 Big Data Clusters, and even show you how to extend and customize the SSIS toolbox using custom-developed tasks and transformations. This ETL book also contains practical recipes for moving and transforming data with Azure services, such as Data Factory and Azure Databricks, and lets you explore various options for migrating SSIS packages to Azure. Toward the end, you will find out how to profile data in the cloud and automate package development with Business Intelligence Markup Language (BIML).

By the end of this book, you will have developed the skills you need to create and automate ETL solutions on-premises as well as in Azure.

작가정보

저자(글) Christian Cote

Christian Cote is an IT professional with more than 15 years of experience working on data warehouse, big data, and business intelligence projects. Christian has developed expertise in data warehousing and data lakes over the years and has designed many ETL/BI processes using a range of tools on multiple platforms. He's presented at several conferences and code camps. He currently co-leads the SQL Server PASS chapter. He is also a Microsoft Data Platform Most Valuable Professional (MVP).

저자(글) Matija Lah

Matija Lah has more than 18 years of experience working with Microsoft SQL Server, mostly from architecting data-centric solutions in the legal domain. His contributions to the SQL Server community have led to him being awarded the Microsoft MVP award (Data Platform) between 2007 and 2017/2018. He spends most of his time on projects involving advanced information management and natural language processing, but often finds time to speak at events related to Microsoft SQL Server where he loves to share his experience with the SQL Server platform.

저자(글) Madina Saitakhmetova

Madina Saitakhmetova is a developer specializing in BI. She has been in IT for 15 years, working with Microsoft SQL, .NET, Microsoft BI, Azure, and building BI solutions for medical, educational, and engineering companies. Her adventure with Microsoft BI began with Analysis Services and SSIS, and in later years she has been building her expertise in ETL/ELT, both on-premises and in the cloud. Finding patterns, automating processes, and making BI teams work more efficiently are challenges that drive her. During the past few years, BIML has become an important part of her work, increasing its efficiency and quality.