Book Image

SAP Data Services 4.x Cookbook

By : Shomnikov
Book Image

SAP Data Services 4.x Cookbook

By: Shomnikov

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 (14 chapters)
11
11. Working with SAP Applications
13
Index

Creating validation functions

One of the ways to implement the data validation process in Data Services is to use validation functions along with the Validation transform in your dataflow to split the flow of data into two: records that pass the defined validation rule and those that do not. Those validation rules can be combined into validation function objects for your convenience and traceability.

In this recipe, we will create a standard but quite simple validation function. We will deploy it in our dataflow, which extracts the address data from the source system into a staging area. The Validation function will check to see whether the city in the migrated record has Paris as a value, and if it does, it will send the records to a separate reject table.

Getting ready

First, we need to create another schema in our STAGE database to contain reject tables. Creating the Reject schema to store these tables allows the keeping of the original table names; that makes writing queries and reporting...