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

Using SSIS fuzzy components


SSIS includes two really sophisticated matching transformations in the data flow. The fuzzy lookup transformation is used for mapping the identities. The fuzzy grouping transformation is used for de-duplicating. Both of them use the same algorithm for comparing the strings and other data.

Identity mapping and de-duplication are actually the same problem. For example, instead for mapping the identities of entities in two tables, you can union all of the data in a single table and then do the de-duplication. Or vice versa, you can join a table to itself and then do identity mapping instead of de-duplication. This recipe shows how to use the fuzzy lookup transformation for identity mapping.

Getting ready

This recipe assumes that you have successfully finished the previous recipe.

How to do it...

  1. In SSMS, create a new table in the DQS_STAGING_DATA database in the dbo schema and name it dbo.FuzzyMatchingResults. Use the following code:
CREATE TABLE dbo.FuzzyMatchingResults...