Pegasystems Inc., the leader in Business Process Management (BPM) and software for customer centricity, today announced integration with Apache Hadoop to enhance its industry-leading predictive and adaptive analytics offering.
 
Working in conjunction with several major customers, Pegasystems completed a successful reference implementation of Hadoop within its environment. The marriage of a big data Hadoop technology with Pega’s adaptive and real-time recommendation engine marks an industry breakthrough for advanced multi-channel customer interactions.
 
The customer database was built on Hadoop with 17,000 selectable items mapped against a database of 2.5 million consumers. The predictive models deployed used multiple profile dimensions including preferences, history and priority. The Pega engine consumed Hadoop-based analytic summaries, and then refined customer preferences with built-in adaptive and predictive analytics. Because the solution manages real-time interactions, the system continuously and dynamically improved the underlying predictive models.
 
“This combination of data-driven recommendations from Hadoop with our highly successful adaptive and self-learning predictive model architecture has generated significantly more insight from raw big data than was previously possible,” said Dr. Rob Walker, Vice President of Decision Management and Analytics at Pegasystems. “Big data is most useful when it’s actionable and used to drive smart decisions. We are thrilled with the competitive advantage that this will give our clients.”
 
“Predictive analytics are becoming more-widely used in intelligent, event-driven business operations,” said Roy Schulte, Vice President and Distinguished Analyst at Gartner. “As the volume of event data grows, and businesses understand the benefits of running more-sophisticated analytics to enable intra-day improvements in their operations, we expect to see more use of MapReduce techniques such as those provided by Hadoop. This is contributing toward the evolution of BPM Suites into next-generation intelligent BPM Suites (iBPMS).”
 
“Pega shows how predictive next best actions can also be put to significant use across all processes and interactions, not just consumer preference recommendations,” said Alan Trefler, Founder and CEO of Pegasystems. “Pega’s Next Best Action Advisor continually incorporates multiple information sources. Its predictive and adaptive models actually learn faster the more data we can feed them, yielding better predictive recommendations even at the point of customer interaction.”

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