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

Building significant columns data profiling scripts


Significant columns are the proposed natural columns you will be using in your dimensions to uniquely identify an individual record for the dimension. These keys determine the grain of the dimension.

Getting ready

Identify all the dimension entities within your semantic data model and determine the source tables for these dimensions.

How to do it...

Significant columns may differ from the natural key of the table:

  1. 1. Connect to the source system using Oracle SQL Developer.

  2. 2. Build a SQL statement to validate the grain of the dimension.

    Sample SQL statement:

    select <attribute_name>, <attribute_name>,
    <attribute_name> , count(*)
    from <schema.table_name>
    group by <attribute_name>, <attribute_name>,
    <attribute_name>;
    

    Sample SQL statement:

    select planner_code, segment1 , count(*)
    from inv.mtl_system_items
    group by planner_code, segment1;
    
  3. 3. Validate the result set.

How it works...

The results which you...