Your project team was organized, the development phases were completed, the testing was done, the data warehouse was deployed, and the project was pronounced completed on time and within budget. Has the effort been successful? In spite of the best intentions of the project team, it is likely that the deployed data warehouse turns out to be anything but a data warehouse. Figure 4-10 shows possible scenarios of failure. How will your data warehouse turn out in the end?

Effective project management is critical to the success of a data warehouse project. In this section, we will consider project management issues as they especially apply to data warehouse projects, review some basic project management principles, and list the possible success factor s. We will review a real-life successful project and examine the reasons for its success. When all is said and done, you cannot always run your project totally by the book. Adopt a practical approach that produces results without getting bogged down in unnecessary drudgery.

4.5.1. Guiding Principles

Having worked on OLTP system projects, you are already aware of some of the guiding principles of project management—do not give into analysis paralysis, do not allow scope creep, monitor slippage, keep the project on track, and so on. Although most of those guiding principles also apply to data warehouse project management, we do not want to repeat them here. On the other hand, we want to consider some ...

Get DATA WAREHOUSING FUNDAMENTALS: A Comprehensive Guide for IT Professionals now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.