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HP Unveils Open-Source Big Data Predictive Analytics Platform

HP Unveils Open-Source Big Data Predictive Analytics Platform Image Credit: Hewlett Packard

HP has unveiled HP Haven Predictive Analytics, a new open-source big data analytics platform offering that aims to accelerate and operationalize large-scale machine learning and statistical analysis, and ultimately provides organizations with much deeper insights and understanding into today’s rapidly evolving data volumes. The platform makes predictive analytics capabilities available to organizations via a standard set of SQL interfaces to access data stored in the HP Vertica database.

The new version of the software includes an enhanced version of R, the statistical modelling language commonly used in big data analytics, which enables developers to address large data sets distributed across multiple clusters, and to make calculations on them as a single entity. HP has built native connectors between Vertica and Distributed R that enable developers to run Distributed R queries from within the database. 

Dr. Doug McNair, M.D., PhD, SVP, Cerner Corporation
HP Haven Predictive Analytics provides the scale and performance to Cerner to achieve predictive analytics health care solutions that were not possible before. The Distributed R technology is vital for Cerner’s discovery activities, which we conduct for Cerner’s health care clients around the world. In health care use cases, the most valuable item sets are rare. Therefore, coverage of the entire corpus of records is often essential to avoid false-negative results and to ensure model stability. HP Haven Predictive Analytics is a strategic enabler for Cerner.

Shilpa Lawande, GM Platform, HP Software Big Data Business Unit
HP Haven Predictive Analytics delivers the industry’s first open, high-performance platform based on R, seamlessly integrated with the HP Haven Big Data Platform. Now, organizations can unlock the untapped value of Big Data with scalable predictive analytics to address every use case – from customer acquisition and retention to fraud detection to predictive maintenance and many more.

Author

Ray is a news editor at The Fast Mode, bringing with him more than 10 years of experience in the wireless industry.

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