Turning utility computing into a service model for analytics.

With the needs of Enterprise Analytics growing at ever increasing speeds, it becomes clear that traditional hub and spoke architectures are in no way able to sustain the demands driven by increasingly complex business analytics. As with any proliferation of systems the overhead of managing, maintaining and developing trees of increasingly complex dependencies quickly out paces the ability of an organization to deal with its challenges. What may work well at first turns into a real evolution nightmare.

It rapidly becomes more and more difficult to react to ongoing changes in business demands and growth. For many years, some of the largest corporations in the world have realized this and have focused on re-integrating islands and stovepipes of information into much more centralized analytical infrastructures.

Quite often however, this is also seen as a step towards reducing flexibility - in terms of time to market - for individual groups to quickly deliver to rapidly changing business demands. It's a very typical love-hate relationship with these so-called departmental systems or data marts.

Great for a localized team to 'bang' out new capabilities, but becomes a data integration nightmare with huge TCO (Total Cost of Ownership) implications, that are quite often not visible to the overall organization.