Book Image

Oracle Data Integrator 11g Cookbook

Book Image

Oracle Data Integrator 11g Cookbook

Overview of this book

Oracle Data Integrator (ODI) is Oracle's strategic data integration platform for high-speed data transformation and movement between different systems. From high-volume batches, to SOA-enabled data services, to trickle operations, ODI is a cutting-edge platform that offers heterogeneous connectivity, enterprise-level deployment, and strong administrative, diagnostic, and management capabilities."Oracle Data Integrator 11g Cookbook" will take you on a journey past your first steps with ODI to a new level of proficiency, lifting the cover on many of the internals of the product to help you better leverage the most advanced features.The first part of this book will focus on the administrative tasks required for a successful deployment, moving on to showing you how to best leverage Knowledge Modules with explanations of their internals and focus on specific examples. Next we will look into some advanced coding techniques for interfaces, packages, models, and a focus on XML. Finally the book will lift the cover on web services as well as the ODI SDK, along with additional advanced techniques that may be unknown to many users.Throughout "Oracle Data Integrator 11g Cookbook", the authors convey real-world advice and best practices learned from their extensive hands-on experience.
Table of Contents (19 chapters)
Oracle Data Integrator 11g Cookbook
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Impacting the data flow by changing the staging area location


When an interface is created, ODI will by default create the staging area on the target server. There are many reasons for this design choice:

  • Data is usually loaded into servers that are larger than the ones data is extracted from: data warehouses for instance will host a lot more data than individual systems, and as a result these systems will tend to offer a lot more processing power.

  • Centralizing data coming from disparate sources is more convenient in a central location. As long as everything has to be loaded on the target system eventually, staging on the target will save us additional data movement.

  • Often times, source systems cannot be used for staging because of restricted permissions (read only).

However, there are cases where staging data away from the target is necessary. For example, if a process writes to a flat file, there is no way to transform data by leveraging the engine on the target side: there is none to use...