Typical data warehouse deployment lifecycle
Posted by Dylan Wan on November 2, 2007
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.
