Book Image

SAP Data Services 4.x Cookbook

Book Image

SAP Data Services 4.x Cookbook

Overview of this book

Want to cost effectively deliver trusted information to all of your crucial business functions? SAP Data Services delivers one enterprise-class solution for data integration, data quality, data profiling, and text data processing. It boosts productivity with a single solution for data quality and data integration. SAP Data Services also enables you to move, improve, govern, and unlock big data. This book will lead you through the SAP Data Services environment to efficiently develop ETL processes. To begin with, you’ll learn to install, configure, and prepare the ETL development environment. You will get familiarized with the concepts of developing ETL processes with SAP Data Services. Starting from smallest unit of work- the data flow, the chapters will lead you to the highest organizational unit—the Data Services job, revealing the advanced techniques of ETL design. You will learn to import XML files by creating and implementing real-time jobs. It will then guide you through the ETL development patterns that enable the most effective performance when extracting, transforming, and loading data. You will also find out how to create validation functions and transforms. Finally, the book will show you the benefits of data quality management with the help of another SAP solution—Information Steward.
Table of Contents (19 chapters)
SAP Data Services 4.x Cookbook
About the Author
About the Reviewers

Creating a custom cleansing package with Cleansing Package Builder

In Chapter 7, Validating and Cleansing Data (see the recipe Data Quality transforms – cleansing your data), we already used the default cleansing package PERSON_FIRM available in Data Services for data cleansing tasks.

In this recipe, we will create a new cleansing package from scratch with the help of Information Steward and publish it so that it can be used in Data Services transforms.

Our new custom cleansing package will be used to determine the type of street used in the address field of the Address table from the OLTP database.

Getting ready

The Information Steward Cleansing Package Builder tool requires a sample flat file with data that is used to define cleansing rules. The following steps describe how to prepare such a flat file with sample data.

As we are going to use our custom cleansing package to cleanse the OLTP.Address table data, we will generate our sample dataset from the same table.

  1. Launch Data Services Designer...