Agile Analytics

Analytics can range from operational reporting, dashboards, scorecard, data mining, and predictive modeling. To be Agile, your processes, technology, and deployment must align and support incremental development. To achieve Agile Analytics, your disparate data must be collected and organized into reporting structures and allow iterative changes without the costly development lifecycle.

In the market today, there are over three dozen reporting tools and a slew of vendors that only sell to the strengths of their product. This falls short of the mark as they only cover operational reporting, dashboards, scorecard, data mining, and predictive modeling. The emphasis should not only be placed on the reporting layer but ensure the data layer is also well organized.

Insight into your data can only become meaningful if your data is organized into suitable business-focused data marts. The data must be collected, modeled, and reported in accordance with your stakeholder’s needs. However, stakeholder’s must interact with the data before requirements can be understood. The traditional requirements approach in long-drawn-out Software Development Lifecycles is not effective. The process must be agile, interactive and iterative.