Book Image

Microsoft SQL Server 2012 Integration Services: An Expert Cookbook

Book Image

Microsoft SQL Server 2012 Integration Services: An Expert Cookbook

Overview of this book

SQL Server Integration Services (SSIS) is a leading tool in the data warehouse industry - used for performing extraction, transformation, and load operations. This book is aligned with the most common methodology associated with SSIS known as Extract Transform and Load (ETL); ETL is responsible for the extraction of data from several sources, their cleansing, customization, and loading into a central repository normally called Data Warehouse or Data Mart.Microsoft SQL Server 2012 Integration Services: An Expert Cookbook covers all the aspects of SSIS 2012 with lots of real-world scenarios to help readers understand usages of SSIS in every environment. Written by two SQL Server MVPs who have in-depth knowledge of SSIS having worked with it for many years.This book starts by creating simple data transfer packages with wizards and illustrates how to create more complex data transfer packages, troubleshoot packages, make robust SSIS packages, and how to boost the performance of data consolidation with SSIS. It then covers data flow transformations and advanced transformations for data cleansing, fuzzy and term extraction in detail. The book then dives deep into making a dynamic package with the help of expressions and variables, and performance tuning and consideration.
Table of Contents (23 chapters)
Microsoft SQL Server 2012 Integration Services: An Expert Cookbook
About the Authors
About the Reviewers

Fuzzy Transformations—how SSIS understands fuzzy similarities

Suppose that input data is a csv file with department name information and there is no guarantee that the department names are spelt consistently. So you may have names such as "Management" and "Managmnt" together in the same data file. In such cases an ordinal Lookup Transform cannot detect these similarities, because Lookup checks for terms that are completely identical. This is where we need to apply some Fuzzy operations.

SSIS has two Fuzzy Transformations, which catch fuzzy similarities between terms and help us in master data management, as follows:

  • Fuzzy Grouping: This component will create groups of data rows based on their similarity threshold

  • Fuzzy Lookup: This component will look at a reference table to find matching keywords based on a predefined similarity threshold

In this recipe, we take a look at two Fuzzy Transformations and how they can help us in real-world scenarios.

Getting ready

Create a Department table with...