“By 2014, 30% of analytic applications will use proactive, predictive and forecasting capabilities”  Gartner Forecast, 2011

Most organizations are starting to think about “analytics-as-a-service” as they struggle to cope with the problem of analyzing massive amounts of data to find patterns, extract signals from background noise and make predictions. In our discussions with CIOs and others, we are increasingly talking about leveraging the private or public cloud computing to build an analytics-as-a-service model.

The strategic goal is to harness data to drive insights and better decisions faster than competition as a core competency.  Executing this goal requires developing state-of-the-art capabilities around three facets:  algorithms, platform building blocks, and infrastructure.