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In an age of demanding customer
expectations and increasingly aggressive competitors, organizations are rapidly
moving from reliance on business intelligence (BI) tools that provide a snapshot
of the past to those that provide an accurate picture of the present and a
prediction of future trends.
Synthesizing massive amounts of historical data as well as up-to-the-minute live
data interactions to determine the
“next-best offer” or predictor is a difficult task.
But companies need to tackle it if they want to meet their business objectives,
which center around competitive
advantage, cost savings, and greater revenues.
The right analytics architecture will play a pivotal role in the success of
predictive analytics, not only providing
companies with current intelligence, but also helping them maximize their
revenue potential during short windows of
We interview Tom Traubitz to gain SAP's perspective on