The single most important design issue facing the data warehouse developer is determining the proper level of granularity of the data that will reside in the data warehouse. When the level of granularity is properly set, the remaining aspects of design and implementation flow smoothly; when it is not properly set, every other aspect is awkward.
Granularity is also important to the warehouse architect because it affects all the environments that depend on the warehouse for data. Granularity affects how efficiently data can be shipped to the different environments and determines the types of analysis that can be done.
The primary issue of granularity is that of getting it at the right level. The level of granularity needs to be neither too high nor too low.
The trade-off in choosing the right levels of granularity (as discussed in Chapter 2) centers around managing the volume of data and storing data at too high a level of granularity, to the point that detailed data is so voluminous that it is unusable. In addition, if there is to be a truly large amount of data, consideration must be given to putting the inactive portion of the data into overflow storage.
The starting point for determining the appropriate level of granularity is to do a raw estimate of the number of rows of data and the DASD (direct access storage device) that will be in the data warehouse. Admittedly, in the best of circumstances, only an estimate can be made. ...