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

Reuse me please - reusable transformation


As you are aware, sources and targets are reusable components, that is, you work on sources in Source Analyzer and targets in Target Designer respectively. Also, you must be aware that you cannot edit sources and targets in Mapping Designer; they can only be edited in Source Analyzer and Target Designer respectively.

Sources and targets are called reusable components because you can use the same source and target in multiple mappings. We can reuse the source or target across multiple mappings only if the metadata requirements of both mappings is exactly the same. Metadata, in this case, means the number of columns, their data type, their data size, indexes, constraints, and so on. Even if there are small changes, you cannot reuse the components.

On the same lines, if we have the same logic to implement across multiple mappings, we can use the reusable transformations, which allow us to reuse the same transformation across mappings. You can only reuse...