AGILE ANALYTICS FOR ADVANCED BI VISUALIZATION, ADVANCED ANALYTICS, AND ELT
I recently gave an Agile Analytics webinar on Agile User Stories for DW/BI Projects, and an attendee emailed me this question afterward: “Would the approach discussed work for Advanced Visualization and Advanced Analytics projects? And project using more of an ELT approach?”
Here is my answer:
By Advanced Visualization I will assume you mean using strong visualization tools like QlikView, Tableau or Spotfire, etc. Many Agile teams are leveraging these in-memory visualization tools to deliver business value quickly AND to provide a working “prototype” that can be built out more robustly in the data warehouse as well.
For example, a client I worked with built out a complex sales dashboard in a few weeks using QlikView. Once they had used it for a period of time and confirmed it’s what they wanted in the long-term, the DW team then “reverse-engineered” the QlikView extracts, calculations, etc. and built them out more robustly in the warehouse. Then they re-pointed QlikView to source data from the DW rather than the CSV files they had been using in the “prototype.” The business just loved using QlikView and they also wanted the robustness that the DW provided for the long-term. Therefore, my answer regarding Advanced Visualization is that yes, Agile can work really well with these tools! In fact, these tools are technical enablers of an agile approach since they provide business value so quickly.
Regarding Advanced Analytics: The more complex and risky a project is, the better-suited it is for Agile since rapid feedback and learning cycles are important when you’re doing something really complex.