Managing BI projects is a difficult responsibility that challenges even the most experienced IT project managers. Source system dependencies, uncertain data quality, volatile business requirements, and business urgency are but a few examples among a multitude of challenges. Many kinds of BI projects, ranging from data integration to predictive analytics, add to the complexities—and multiple technologies from data warehousing to data mining compound the problem. With BI projects, there is no project management silver bullet—no “one size fits all” approach to project management. Learn how to choose among traditional, agile, and other project management methods. Then find out how to apply the chosen method for project planning, execution, monitoring, control, completion, and closure.
You Will Learn
- Why and how managing BI projects is more difficult than managing traditional IT projects
- How to define a manageable BI project
- How to choose among traditional, agile, and rational unified project management methods
- How to combine methods to create a hybrid approach to BI project management
- How to plan a project with each project management method
- How to apply each method in project execution
- How each method supports project monitoring and control
- How to apply each method at project completion