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

Introduction

In this chapter we move to the most important component of the ETL design in Data Services: the dataflow object. The dataflow object is the container that holds all transformations that can be performed on data.

The structure of the dataflow object is simple: one or many source objects are placed, on the left-hand side (which we extract the data from), then source objects are linked to the series of transform objects (which perform manipulation on the data extracted), and finally, the transform objects are linked to one or many target table objects (telling Data Services where the transformed data should be inserted). During the transformation of the dataset inside the dataflow, you can split the dataset into multiple dataset flows, or conversely, merge multiple separately transformed dataflows together.

Manipulations performed on data inside dataflows are done on a row-by-row basis. The rows extracted from the source go from left to right through all objects placed inside the...