'Zementis for IBMz' - A New Predictive Analytic Solutions for Businesses
SAN DIEGO, CA: Zementis and IBM Corporation announced a joint strategic initiative and corresponding technology solution, “Zementis for IBM Z Systems” designed for companies to make effective business decisions and faster implementations. By integrating predictive analytics capabilities directly into transactional data flows, the solution seeks to unlock the full potential of an organization’s data assets and business processes.
Zementis’ solution for high-speed development, deployment and operation of predictive analytics models with IBM z Systems, help organizations reinvent enterprise IT to become digital businesses. The solution integrates enterprise-grade predictive analytics into the IBM z Systems z/OS data lifecycle ecosystem. The joint solution represents a family of certified products that enable exceptionally fast operational deployment and embedded scoring functionality of predictive models in key transaction environments, including but not limited to CICS and WebSphere for z/OS.
By integrating analytics and transaction processing which increases customer value with every interaction, organizations can: Increase business flexibility through accurate insights delivered at the right time and point of impact; improve data governance and security by integrated software, hardware and business processes and reduce infrastructure cost and complexity through streamlined architecture and business processes
The solution achieves these results by: Providing insights via in-line predictive analytics, maintaining the integrity of supported business processes via in-transaction processing, scoring thousands of data records per second, balancing business needs to enable instant decisions, improving performance and cost efficiency by reducing or eliminating movement of data off-platform to conduct analysis.
Available from August 2015, the solution also maximizes the value of existing IT infrastructure to drive capital efficiency, enhancing governance and security, not just of the data, but also of the predictive analytics. It broadens consistency and assures compatibility across data mining tools with PMML industry standard.