Project plans for data warehouses

Project plans for data warehouses

We all intellectually understand that data warehousing is an iterative, not a waterfall, process. Actually, anyone who's been through a successful project or two can attest to this from personal experience. Strict adherence to a project plan with linear development can spell disaster for data warehouse projects. Many well-meaning data warehouse project managers will construct just such a project plan and end up either scrapping the project planning period, taking the project into the untrackable zone, or will stick it out until the bitter end. So, isn't there a place for a project plan in data warehousing? There absolutely is, with these caveats that accommodate its iterative nature:

  1. Major items, like data modeling, source-target modeling, end-user environment setup, source system analysis, etc. have 3-4 development cycles.
  2. Each of these development cycles are actually full deliverables (like a complete data model) and not just steps in the process of delivering the item.
  3. The complete cycles run until the deliverable can be considered final and therefore there may be more (or fewer) cycles than the 3-4 on the initial plan.
  4. Major activities run in parallel and are allowed to start when resources can get to it instead of waiting for other activities to complete. Seldom will this result in wasted effort.

As a consequence of #1 above, most appropriate data warehouse project plans are much larger than what

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you'd expect. But don't get lost in the trees. See the forest too. Pull out major tasks as milestones for upper management status reporting and to maintain a true understanding of the overall effort's progress.


This was first published in October 2001

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