Wednesday, November 12, 2014

IBM and Zementis Release White Paper: "Enhancing Predictive Analytics"

Continuing their longstanding partnership, Zementis and IBM recently released a white paper that details how organizations can improve their business agility through predictive analytics. The paper describes some of the key benefits that organizations can derive from applying predictive analytics to key decisions, outlines some of the operational and technical challenges that organizations commonly face in this effort, and showcases the capabilities that IBM and Zementis make possible to unlock the full potential of big data through predictive analytics.

Together, Zementis and IBM help enterprises overcome many challenges associated with their big data efforts, simplifying and accelerating the deployment of predictive models and making possible large-scale analytics that once seemed impractical to execute.

Zementis' UPPITM solution is integrated with several of IBM's flagship big data analytics platforms, including IBM PureDataTM System for Analytics, powered by Netezza® technology, and IBM InfoSphere® BigInsightsTM software. In each case, the joint IBM/Zementis solution helps companies deploy, execute and integrate scalable, standards-based predictive analytics. UPPI extends the in-database and Hadoop-based predictive analytics capabilities of these IBM platforms through the use of Hive, a data warehouse system for Hadoop.

The white paper describes the benefits of Zementis' open standards approach to predictive analytics, as well as the technical capabilities of the joint solutions with IBM and the tangible benefits that organizations can realize by making IBM and Zementis a foundational element of their big data analytics strategy and architecture.

Highlights of the joint solution include:
  • Enables near real-time predictive model deployment through a universal, flexible approach
  • Reduces cost and complexity of deploying and utilizing predictive analytics for big data
  • Delivers standards-based execution of predictive analytics for in-database scoring
  • Accelerates time-to-market for enhancing intelligent decision making via predictive data
  • Supports highly dynamic and complex data environments with massively parallel processing
  • Extends the analytics functionality and business value of robust IBM platforms
Download the white paper

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