This is part 1 of a 6-part series of articles discussing how a Data Warehouse Bus Matrix can be used to Design, Plan, Estimate and Share the scope, coverage, status, effort and progress of your Data Warehouse project.
The industry-accepted method of modelling a Data Warehouse is to use a star schema described in the "Kimball" method. This method underpins most commercial data warehouses. In the Kimball method, practitioners are encouraged to develop a "Data Warehouse Bus Matrix" to describe the high-level design of the Data Warehouse.
Below is an example of a very simple Data Warehouse Matrix.
On the rows of the Matrix are the Facts/Business Processes (e.g. Sales). On the columns are the Dimensions/Business Entities (e.g. Customer). The cells represent the relationships between the Facts and Dimensions. The number represents how many relationships exist between the Fact and Dimension.
For example, the "Production" fact below is related to (or dimensioned by) the Dimensions Product, Staff and Calendar. This means an end-user can analyze "Production" measures by any combination of the Product, Staff, or Calendar Dimensions attributes.
A Data Warehouse Matrix is a simple yet powerful communication tool. Its simplicity is its core strength, making it useful for communication that works at every level of the organization, from executives to end-users and developers.
A Data Warehouse matrix serves several purposes:
1. Capture Design: Succinctly capture the high-level design of the enterprise-wide data warehouse.
2. Communication: At a glance, communicate the scope, business process coverage and high-level design of the Data Warehouse to stakeholders, developers and end-users.
3. Estimate: With a few enhancements, Designers can use the Data Warehouse matrix to estimate the time required to build the Data Warehouse.
4. Plan: Assist in planning the delivery of each development iteration of the project whilst ensuring each iteration conforms to an overall design.
5. Progress: Communicate the progress of the project.
The next articles in this series dig deeper into each of these purposes.
