Book Image

SQL Server 2017 Integration Services Cookbook

By : Christian Cote, Dejan Sarka, David Peter Hansen, Matija Lah, Samuel Lester, Christo Olivier
Book Image

SQL Server 2017 Integration Services Cookbook

By: Christian Cote, Dejan Sarka, David Peter Hansen, Matija Lah, Samuel Lester, Christo Olivier

Overview of this book

SQL Server Integration Services is a tool that facilitates data extraction, consolidation, and loading options (ETL), SQL Server coding enhancements, data warehousing, and customizations. With the help of the recipes in this book, you’ll gain complete hands-on experience of SSIS 2017 as well as the 2016 new features, design and development improvements including SCD, Tuning, and Customizations. At the start, you’ll learn to install and set up SSIS as well other SQL Server resources to make optimal use of this Business Intelligence tools. We’ll begin by taking you through the new features in SSIS 2016/2017 and implementing the necessary features to get a modern scalable ETL solution that fits the modern data warehouse. Through the course of chapters, you will learn how to design and build SSIS data warehouses packages using SQL Server Data Tools. Additionally, you’ll learn to develop SSIS packages designed to maintain a data warehouse using the Data Flow and other control flow tasks. You’ll also be demonstrated many recipes on cleansing data and how to get the end result after applying different transformations. Some real-world scenarios that you might face are also covered and how to handle various issues that you might face when designing your packages. At the end of this book, you’ll get to know all the key concepts to perform data integration and transformation. You’ll have explored on-premises Big Data integration processes to create a classic data warehouse, and will know how to extend the toolbox with custom tasks and transforms.
Table of Contents (18 chapters)
Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Introduction


Data warehouse architects are facing the need to integrate many types of data. Cloud data integration can be a real challenge for on-premises data warehouses for the following reasons:

  • The data sources are obviously not stored on-premises and the data stores differ a lot from what ETL tools such as SSIS are usually made for. As we saw earlier, the out-of-the-box SSIS toolbox has sources, destinations, and transformation tools that deal with on-premises data only.
  • The data transformation toolset is quite different to the cloud one. In the cloud, we don't necessarily use SSIS to transform data. There are specific data transformation languages such as Hive and Pig that are used by the cloud developers. The reason for this is that the volume of data may be huge and these languages are running on clusters. as opposed to SSIS, which is running on a single machine.

While there are many cloud-based solutions on the market, the recipes in this chapter will talk about the Microsoft Azure...