Technology Blog

Typically, organizations will experiment with the concept of data analysis and educate themselves on the value of a data warehouse, prior to determining that a data warehouse is the appropriate solution. In practice, many organizations address this by sponsoring an initial prototyping activity, which is used to further understanding of the feasibility and benefits of a data warehouse. This activity is valuable, and should be considered if this is the organization’s first exposure to the benefits of decision support information.

In some instances, the data warehouse may be the first large-scale client-server solution being implemented within the organization, and will require new skills, experiences, hardware, etc. A prototyping activity on a small scale can further the educational processes as long as the prototype addresses a clearly defined technical objective; the prototype can be thrown away once the feasibility of the concept has been shown - that is, it does not become “the first bit of the data warehouse”; the activity addresses a small subset of the eventual data content of the data warehouse and the activity timescale is non-critical that is, it is seen as a time boxed effort to come to grips with the new technologies being considered.

Unlike prototypes, working models suffer in that they have a tendency to set the expectation that they will grow to the full data warehouse. This may be inappropriate in practice, because the architecture of the model may not scale up to a full data warehouse. If the requirement is to produce an early release of part of a data warehouse, in order to deliver business benefits, we suggest that you focus on the business requirements and technical blueprint phases and understand the short and medium term requirements of the data warehouse.