Book Image

Business Intelligence Cookbook: A Project Lifecycle Approach Using Oracle Technology

By : John Heaton
Book Image

Business Intelligence Cookbook: A Project Lifecycle Approach Using Oracle Technology

By: John Heaton

Overview of this book

Oracle Database 11g is a comprehensive database platform for data warehousing and business intelligence that combines industry-leading scalability and performance, deeply-integrated analytics, and embedded integration and data-quality all in a single platform running on a reliable, low-cost grid infrastructure. This book steps through the lifecycle of building a data warehouse with key tips and techniques along the way. Business Intelligence Cookbook: A Project Lifecycle Approach Using Oracle Technology outlines the key ways to effectively use Oracle technology to deliver your business intelligence solution. This is a practical guide starting with key recipes for project management then moving onto project delivery. Business Intelligence Cookbook: A Project Lifecycle Approach Using Oracle Technology is a practical guide for performing key steps and functions on your project. This book starts with setting the foundation for a highly repeatable efficient project management approach by assessing your current methodology to see how suitable it is for a business intelligence program. We also learn to set up the project delivery phases to consistently estimate the effort for a project. Along the way we learn to create blueprints for the business intelligence solution that help to connect and map out the destination of the solution. We then move on to analyze requirements, sources, and data. Finally we learn to secure the data as it is an important asset within the organization and needs to be secured efficiently and effectively.
Table of Contents (21 chapters)
Business Intelligence Cookbook: A Project Lifecycle Approach Using Oracle Technology
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface

Adding Standard columns to your data model


Each data model requires additional columns other than the columns requested by the solution.

Getting ready

Identify your dimensions and facts within your data model.

How to do it...

Tracking changes in a BI data model is a little different to a standard database application. In the BI data model, we track the process which created or updated the database and not the actual user:

  1. 1. For facts and dimensions, we will want to track when changes were made and by whom. For this, we need to add the standard audit columns. Double-click on the entity, select Attributes, and add the following columns:

    • Create By — Domain — Varchar 32 Characters — specifies which process or mapping created the record.

    • Create Date — Domain — Date — specifies the date the record was created.

    • Update By — Varchar 32 Characters — specifies which process or mapping updated the record.

    • Update Date — Date — specifies the date the record was updated.

  2. 2. Additional attributes to track...