The value proposition of data warehousing/business intelligence (DW/BI) is compelling. However, the business community commonly voices concerns regarding lengthy project timelines, high costs and deficient functionality of initial deliverables.
Agile development methodology has emerged as a ‘faster, cheaper and better’ alternative for delivering business value. When most people think of Agile they associate it with:
- Close collaboration between development and user communities throughout the project life cycle,
- Rapid, iterative prototypes (sprints) to drive out requirements via hands-on interaction with earlier prototypes,
- Frequent, short team meetings (scrums) to identify and mitigate project roadblocks.
These are certainly beneficial behaviors that accelerate delivery of a solution to a specific problem. The objective of any Agile project is to “fail fast” to flush out issues quickly as well as provide incremental progress to stakeholders.
However, without appropriate controls in place, faster delivery can lead to non-integrated point solutions. Over time, this approach can proliferate redundant data and processing affording minimal leverage for future development. Moreover, redundant, conflicting data erodes the very integrity of enterprise business intelligence.
Data integration is not an inevitable compromise for fast delivery. The apparent dilemma stems from the perception by some (not all) that data modeling techniques and architecture discipline are:
- A luxury one cannot afford on Agile projects
- Or a bureaucracy inconsistent with Agile Manifesto that must be avoided under all circumstances
Neither of these perceptions are true. Data modeling can accelerate development and reduce ambiguity and inconsistences in source data, thereby reducing the number and complexity of sprints necessary to solve the business problem.
Compliance with architecture standards yields durable, reusable data and procedures that can be leveraged by subsequent Agile projects. As with any project, performing the work correctly the first time will always be cheaper and faster than starting over.
Embracing modeling and architecture discipline within an Agile project requires a conscious shift in approach and mindset. The necessary changes to the approach and other critical success factors will be discussed in ‘The Challenge with Agile BI, Part 2’.
Are you ready to discuss your project?
Let's chat about it, we look forward to helping and becoming your data partner.
About the Author:
Dr. Robert Conway is the founder and Principal consultant of Information Engineering Associates. He has built successful DW/BI programs for many organizations in diverse industries. He offers public and onsite workshops on RAPID® Architecture/Methodology and Data Modeling skills. www.InfoEngAssc.com