Data Warehousing Special Topic (23): Alternative application of bus matrix-drill down to a more detailed bus matrix

First, preface

Many of you is already familiar with the Data Warehouse bus architecture and matrix given their central role in building architected data marts. The corresponding bus matrix identifies the key business processes of a organization, along with their associated Dimensi Ons. Business processes (typically corresponding to major source systems) is listed as matrix rows, while dimensions appear as Matrix columns. The cells of the matrix is then marked to indicate which dimensions apply to which processes.

In a single document, the Data Warehouse team have a tool for planning the overall data warehouse, identifying the shared D Imensions across the enterprise, coordinating the efforts of separate implementation teams, and communicating the Importan Ce of shared dimensions throughout the organization. We firmly believe drafting a bus matrix is one of the key initial tasks to being completed by every data Warehouse team after Soliciting the business ' requirements.

Ii. facing the problem

While the matrix provides a high-level overview of the Data Warehouse presentation layer "puzzle pieces" and their ultimat e linkages, it is often helpful to provide more detail as each matrix row is implemented. Multiple fact tables often result from a single business process. Perhaps there ' s a need to view business results in a combination of transaction, periodic snapshot or accumulating Snapsho T perspectives. Alternatively, multiple fact tables is often required to represent atomic versus more summarized information or to Suppor T richer analysis in a heterogeneous product environment.

Third, the solution

We can alter the matrix ' s "grain" or level of detail so, each row represents a single fact table (or cube) related to A business process. Once we ' ve specified the individual fact table, we can supplement the matrix with columns to indicate the fact table s GRA Nularity and corresponding facts (actual, calculated or implied). Rather than merely marking the dimensions that apply to each fact table, we can indicate the dimensions ' level of detail ( such as brand or category, as appropriate, within the Product dimension column).

Iv. Summary

The resulting embellished matrix provides a roadmap to the families of fact tables in your Data warehouse. While many of us is naturally predisposed to dense details, we suggest your begin with the more simplistic, high-level mat Rix and then drill-down to the details as each business process is implemented. Finally, for those of a existing data warehouse, the detailed matrix was often a useful tool to document the "as Is ' status of a more mature warehouse environment.

Data Warehousing Special Topic (23): Alternative application of bus matrix-drill down to a more detailed bus matrix