Chapter 1, Introduction to SQL Server 2017, very briefly covers the most important features and enhancements, not just those for developers. The chapter shows the whole picture and points readers in the direction of where things are moving.
Chapter 2, SQL Server Tools, helps you understand the changes in the release management of SQL Server tools and explores small and handy enhancements in SQL Server Management Studio (SSMS). It also introduces RStudio IDE, a very popular tool for developing R code, and briefly covers SQL Server Data Tools (SSDT), including the new R Tools for Visual Studio (RTVS), a plugin for Visual Studio, which enables you to develop R code in an IDE that is popular among developers using Microsoft products and languages. The chapter introduces Visual Studio 2017 and shows how it can be used for data science applications with Python.
Chapter 3, JSON Support in SQL Server, explores the JSON support built into SQL Server. This support should make it easier for applications to exchange JSON data with SQL Server.
Chapter 4, Stretch Database, helps you understand how to migrate historical or less frequently/infrequently accessed data transparently and securely to Microsoft Azure using the Stretch Database (Stretch DB) feature.
Chapter 5, Temporal Tables, introduces support for system-versioned temporal tables based on the SQL:2011 standard. We explain how this is implemented in SQL Server and demonstrate some use cases for it (for example, a time-travel application).
Chapter 6, Columnstore Indexes, revises columnar storage and then explores the huge improvements relating to columnstore indexes in SQL Server 2016: updatable non-clustered columnstore indexes, columnstore indexes on in-memory tables, and many other new features for operational analytics.
Chapter 7, 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 8, 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 9, 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 10, 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 11, 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 12, 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 13, 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 14, 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.
