Data warehouse projects pose a specific set of challenges for the project manager. Whilst most IT projects are a development to support a well defined pattern of work a data warehouse is, by design, there to support users asking ad hoc questions of the data available to the business. It is also a project that will have more interfaces and more change than any other system within the organisation.
Projects often have poorly set expectations in terms of timescales; the likely return on investment, the vendors’ promises for tools or the expectations set between the business and IT within an organisation. They also have large technical architectures and resourcing issues that need to be handled.
This document will outline the building blocks of good project control including the definition of phases, milestones, activities, tasks, issues, enhancements, test cases, defects and risks and will discuss how they can be managed, and when, using an event horizon, the project manager can expect to get information.
To help manage these building blocks this paper will look at the types of tools and technology that are available and how they can be used to assist the project manager. It also looks at how these tools fit into methodologies.
The final section of the paper has looked at how effective project leadership and estimating can improve the chances of success for a project. This includes understanding the roles of the executive sponsor, project manager, technical architect and senior business analyst along with the use of different leadership styles, organisational learning and team rotation.
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