Chapter 1, SSIS Setup, contains recipes describing the step by step setup of SQL Server 2016 to get the features that are used in the book.
Chapter 2, What Is New in SSIS 2016, contains recipes that talk about the evolution of SSIS over time and what's new in SSIS 2016. This chapter is a detailed overview of Integration Services 2016, new features.
Chapter 3, Key Components of a Modern ETL Solution, explains 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. This chapter will also describe what each catalog view provides and will help you learn how you can use some of them to archive SSIS execution statistics.
Chapter 4, Data Warehouse Loading Techniques, describes many patterns used when it comes to data warehouse or ODS load. You will learn how to effectively load a data warehouse and process a tabular model, maintain data partitions and modern data refresh rates.
Chapter 5, Dealing with Data Quality, focuses on how SSIS can be leveraged to validate and load data. You will learn how to identify invalid data, cleanse data and load valid data to the data warehouse.
Chapter 6, SSIS Performance and Scalability, will talk about how to monitor SSIS package execution. It will also provide solutions to scale out processes by using parallelism. You will learn how to identify bottlenecks and how to resolve them using various techniques.
Chapter 7, Unleash the Power of SSIS Script Task and Component, covers how to use scripting with SSIS. You will 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, talks about how SSIS can be used to prepare the data you need for further analysis. Here, you will learn how you can make use of SQL Server Analysis Services (SSAS) and R models in the SSIS data flow.
Chapter 9, On-Premises and Azure Big Data Integration, describes the Azure feature pack that allows SSIS to integrate Azure data from blob storage and HDInsight clusters. You will learn how to use Azure feature pack components to add flexibility to their SSIS solution architecture and integrate on-premises Big Data can be manipulated via SSIS.
Chapter 10, Extending SSIS Tasks and Transformations, talks about extending and customizing the toolbox using custom developed tasks and transforms and security features. You will learn the pros and cons of creating custom tasks to extend the SSIS toolbox and secure your deployment.
Chapter 11, Scale Out with SSIS 2017, talks about scaling out SSIS package executions on multiple servers. You will learn how SSIS 2017 can scale out to multiple workers to enhance execution scalability.
