In our first post of this series, we discussed how to identify opportunities where Agile can be used in BI\DW enterprise initiatives and how to begin planning for implementation. So you have an eager agile team, prioritized business functionality, a system design, an invested business owner, and a desire to make each iteration better than the last. Smooth sailing from here on out, right? Unfortunately, that isn’t usually case. Every project, including BI/DW projects, will have pitfalls and challenges. However, you can avoid these pitfalls and gracefully face these challenges with some lessons learned and best practices derived from the experience of teams who have successfully made the leap to agile BI/DW.
Agile methodologies, such as Scrum and Extreme Programming (XP), have grown in popularity in recent years for software development projects. Typically, these projects are thought of as endeavors to build stand-alone, packaged products or applications. Less common is the use of agile approaches to build out complex enterprise scale solutions that involve multiple disparate corporate applications. But, in fact, agile methodologies can be extended beyond the “packaged product”. Prominent examples of this are business intelligence and data warehousing (BI/DW) applications where the central technical objective is centralizing and conforming large sets of data to uniform definitions.