Chapters 6 and 7 cover the topic of dimensional data modeling, and they do a pretty good job in outlining the different scenarios one may face when designing a DW. To further help you with dimensional modeling I posted extra examples and videos on Canvas. This is a very important task because the data model constraints and facilitates the types of analyses that you are able to do later on. It is therefore crucial to get it right.
Tasks for this week:
1. I would like you to focus on the organization you used for the previous discussion/s and to produce a preliminary data model for one of it’s key processes or KPIs (may be posted as an attachment if you want):
(a) Identify a measure of interest (KPI), and outline several (1-5) key reports that you expect to be generated with your DW on this measure.
(b) Come up with a single star schema focusing on this measure of interest (at least one fact table and several dimensions) that address the reporting needs you state in (a). The dimensions may be decomposed as needed (snow-flaking /outboard tables – see my PPTs for permissible snow-flaking, and dealing with changing dimensions).
(c) Explain your snow-flaking and granularity considerations.
