A good friend of mine switched from managing non-IT projects to managing a data integration and reporting project. The overall project management methodology is consistent at her company for IT versus non-IT projects. The templates, forms and checklist are all very similar. But as we got to talking, I started thinking about what makes IT project management, specifically of projects that contain data integration and reporting, different and difficult.
Successful projects have a useful project plan that helps the PM keep track of tasks, report status and percent complete. Dependencies on interfaces are key to data integration projects with a reporting component. Interfaces can be defined as both inputs and downstream feeds or reports. Proper lead times and contingency planning are important to avoid delays that can be caused when source data is not ready at the appropriate time in a project. Understand the options if a source system needs to push back a delivery date and examine other options to keep the team moving. For example, can source data be created by the development team for unit testing? Can other pieces of the project be shifted to keep resources busy while waiting on feeds? Integration and communication with downstream systems is important to project success as well. Feedback from those downstream systems about data quality and format should be addressed and the proper adjustments should be made. Expect these types of issues, and build time into the project for iterations. Report development is not dependent on data integration success, only on data model completion. Having reports built and tested with mocked-up data can help uncover potential data model issues before the coding for extract, transform and load is complete - which can be a huge benefit. Do not wait until data integration work is complete to start report development.
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