Book Image

Learning Informatica PowerCenter 10.x - Second Edition

By : Rahul Malewar
Book Image

Learning Informatica PowerCenter 10.x - Second Edition

By: Rahul Malewar

Overview of this book

Informatica PowerCenter is an industry-leading ETL tool, known for its accelerated data extraction, transformation, and data management strategies. This book will be your quick guide to exploring Informatica PowerCenter’s powerful features such as working on sources, targets, transformations, performance optimization, scheduling, deploying for processing, and managing your data at speed. First, you’ll learn how to install and configure tools. You will learn to implement various data warehouse and ETL concepts, and use PowerCenter 10.x components to build mappings, tasks, workflows, and so on. You will come across features such as transformations, SCD, XML processing, partitioning, constraint-based loading, Incremental aggregation, and many more. Moreover, you’ll also learn to deliver powerful visualizations for data profiling using the advanced monitoring dashboard functionality offered by the new version. Using data transformation technique, performance tuning, and the many new advanced features, this book will help you understand and process data for training or production purposes. The step-by-step approach and adoption of real-time scenarios will guide you through effectively accessing all core functionalities offered by Informatica PowerCenter version 10.x.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
Acknowledgement
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Union transformation


Union transformation is used to the merge data from multiple sources. A union is a multiple-input-single-output transformation. This is the opposite of the router transformation that we discussed earlier. The basic criterion for using union transformation is that you should have data with matching data type. If you do not have data with matching data type coming from multiple sources, union transformation will not work. Union transformation merges the data coming from multiple sources and does not remove duplicates, that is. it acts as UNION ALL of SQL statements.

As mentioned previously, Union requires data coming from multiple sources. It reads the data concurrently from multiple sources and processes the data. You can use heterogeneous sources to merge the data using Union transformation.

A mapping indicating the Union transformation is shown in the following screenshot:

Working on Union transformation is a little different from working on other transformations, which...