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

Loading the data warehouse using the framework


This section of the chapter will focus on data warehouse refresh types. The recipes we'll be working through will show you how data is usually refreshed in a data warehouse. This section will basically cover the following topics:

  • Full historical load: This type of loading technique is usually used once to initialize the data warehouses when they are empty
  • Incremental loads: This only loads changes in the source into the data warehouse
  • Near real-time loads (on demand): This is usually used to refresh specific tables with the latest changes for reporting

This recipe will show how the data warehouse loads data in batches. The load programs (SSIS packages) are triggered via a schedule. You'll see that all the packages use the framework to filter the data loaded into the staging. This is the basis of the incremental load that we're going to implement in the data warehouse packages.

Getting ready

This section assumes you have downloaded the solution files...