Big Data

Slay The Data-Overload Dragon With Distributed Processing

Download Now Date Added: Jan 2010
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A large financial services organization using SAS to manually create models had a 92 percent accuracy in its cross-sell predictions. It moved to a data mining solution using "Distributed processing" and saw its accuracy improve to about 98 percent. Distributed processing is a way to accelerate traditional data processing, making predictive CRM more attainable by more businesses. The problem of "Data overload" is a major one faced by anyone with a CRM system. According to a November 2002 survey by Gartner, executives at 90 percent of companies surveyed said they suffered from information overload and that it weakened their competitiveness.