Key Roles involved in a BI Data Warehouse Project

To develop or deploy a BI solution for your organizations, you need to have the right people involved in the time time. Here are typical roles involved in a BI data warehouse project.

• Project Sponsor
• Project Manager
• Functional Analyst
• SME
• BI Architect
• ETL Developers
• DBA

The job description and responsibilities are listed in this table:

DSS and BI

I found a very old book, called Decision Support Systems: An Organizational Perspective, in a library last weekend. It was written by Peter Keen, an author of several popular books, which help many business managers and users understand the value of information technology. His DSS book draw my attention because he is also the author of my textbook Network in Actions.

Typical data warehouse deployment lifecycle

Here is the typical lifecycle for data warehouse deployment project:

0. Project Scoping and Planning

Project Triangle - Scope, Time and Resource.

• Determine the scope of the project - what you would like to accomplish? This can be defined by questions to be answered. The number of logical star and number of the OLTP sources
• Time - What is the target date for the system to be available to the users
• Resource - What is our budget? What is the role and profile requirement of the resources needed to make this happen.

1. Requirement

• What are the business questions? How does the answers of these questions can change the business decision or trigger actions.
• What are the role of the users? How often do they use the system? Do they do any interactive reporting or just view the defined reports in guided navigation?
• How do you measure? What are the metrics?

2. Front-End Design

• The front end design needs for both interactive analysis and the designed analytics workflow.
• How does the user interact with the system?
• What are their analysis process?

3. Warehouse Schema Design

• Dimensional modeling - define the dimensions and fact and define the grain of each star schema.
• Define the physical schema - depending on the technology decision. If you use the relational tecknology, design the database tables

4. OLTP to data warehouse mapping

• Logical mapping - table to table and column to column mapping. Also define the transformation rules
• You may need to perform OLTP data profiling. How often the data changes? What are the data distribution?
• ETL Design -include data staging and the detail ETL process flow.

5. Implementation

• Create the warehouse and ETL staging schema
• Develop the ETL programs
• Create the logical to physical mapping in the repository
• Build the end user dashboard and reports

6. Deployment

• Install the Analytics reporting and the ETL tools.
• Specific Setup and Configuration for OLTP, ETL, and data warehouse.
• Sizing of the system and database
• Performance Tuning and Optimization

7. Management and Maintenance of the system

• Ongoing support of the end-users, including security, training, and enhancing the system.
• You need to monitor the growth of the data.

PeopleSoft EPM

PeopleSoft Enterprise Performance Management was the pre-packaged BI applications for PeopleSoft application.  It has been in market for nearly 10 year.  I recently learned its history, product coverage and architecture from my colleagues.