Book Image

Oracle Business Intelligence 11g R1 Cookbook

By : Cuneyt Yilmaz
Book Image

Oracle Business Intelligence 11g R1 Cookbook

By: Cuneyt Yilmaz

Overview of this book

<p>Extracting meaningful and valuable business information from transactional databases is crucial for any organization. OBIEE 11g is a reporting tool that satisfies all the business requirements regarding complex reporting. It consists of a powerful back-end engine with a repository and a highly customizable graphical web interface.</p> <p>Oracle Business Intelligence 11g R1 Cookbook provides all the key concepts of the product including the architecture of the BI Server. This practical guide shows each and every step of creating analytical reports starting from building a well-designed repository. You will learn how to create analytical reports that will support different business perspectives. <br /><br />This practical guide covers how to implement OBIEE 11g suite in order to enable BI developers to create sophisticated web based reports. All of tasks will be covered step by step in detail. <br /><br />You will explore the architecture of the Oracle Business Intelligence Server and learn how to build the repository (RPD). We will also discuss how to implement the business rules in the repository with real-life scenarios.</p> <p>Best practices of a successful BI implementation are esssential for any BI developer so they are also covered in depth.If you are planning to implement OBIEE 11g suite, this step-by-step guide is a must have resource.All the key tasks are defined in detail and supported with diagrams and screenshots.</p>
Table of Contents (19 chapters)
Oracle Business Intelligence 11g R1 Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Introduction


As a general practice, the data warehouse is maintained at the lowest granular level. Data warehouse performance bottlenecks are often due to measure aggregation. For example, to have some amount of dollars at different levels of dimension hierarchy, a calculation will be needed at runtime. This will impact the performance. Business users should wait for the result set until the calculation regarding the required aggregation is done. Based on the amount of data, the calculations at runtime will be very resource intensive.

So in order to improve the performance of the queries, we're going to use aggregate tables (summary tables). Aggregate tables store precomputed measure values that have been aggregated at different levels of hierarchies. These tables will make the queries run faster. After having aggregate tables, the queries won't consume as much hardware resources as before.