I coauthored my 15th book
Together with Christian Cote (lead author) and Matija Lah (coauthor) we publishes SQL Server 2017 Integration Services Cookbook. Of course, it is kind of early to say this is a definitive guide to SSIS 2017. More accurate name would be SSIS 2016 / 2017 Cookbook. Besides detailed guidelines how to use the 2016 version, you will also find a chapter on some new information on scaling out SSIS 2017. In the future, we will add an online chapter, if it will be needed, about additional new SSIS 2017 functionalities. Anyway, here is a brief description of the chapters.
Chapter 1: SSIS Setup
This chapter will describe step by step how to setup SQL Server 2016 to get the features that are used in the book.
Chapter 2: What is New in SSIS 2016
This chapter is an overview of Integration Services 2016 new features. Some of the topics covered here are covered extensively later in the book.
Chapter 3: Key Components of a Modern ETL Solution
This chapter will explain how ETL has evolved over the past few years and will explain what components are necessary to get a modern scalable ETL solution that fits the modern data warehouse.
Chapter 4: Data Warehouse Loading Techniques
This chapter describes many patterns used when it comes to data warehouse (DW) or operational data store (ODS) load.
Chapter 5: Dealing with Data Quality
This chapter will describe how SSIS, DQS and MDS can be leveraged to validate, cleanse, maintain, and load data.
Chapter 6: SSIS Performance and Scalability
This chapter talks about how to monitor SSIS package execution. It also provides solutions to scale out processes by using parallelism. Readers learn how to identify bottlenecks and how to resolve them using various techniques.
Chapter 7: Unleash the Power of SSIS Script Task and Component
Readers learn how script tasks and script components are very valuable in many situations to overcome the limitations of stock toolbox tasks and transforms.
Chapter 8: SSIS and Advanced Analytics
This chapter talks about using SSIS to prepare data for and do advanced analyses like data mining, machine learning, and text mining. Readers learn how sampling components can be used for preparing the training and the test set, how to use SQL Server Analysis Services data mining models, how to execute R code inside SSIS, and how to analyze texts with SSIS.
Chapter 9: On-Premises and Azure Big Data Integration
This chapter talks about the Azure Feature pack that allows SSIS to integrate Azure data from blob storage and HDInsight clusters. Readers learn how to use Azure feature pack components to add flexibility to their SSIS solution architecture.
Chapter 10: Extending SSIS Custom Task and Transformations
This chapter talks about extending and customize the toolbox using custom developed tasks and transforms.
Chapter 11: Scale Out with SSIS 2017
The last chapter is dedicated to SSIS 2017 and teaches you how to scale out SSIS package executions on multiple servers.
Enjoy the reading!