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  • November 2, 2007

Data Warehouse Project 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.

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