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Creating and Deploying Predictive Strategies that Drive Customer Value in Marketing, Sales and Risk

Scoring Engine

KnowledgeSERVER® is a robust data mining and scoring engine. It provides comprehensive support for organizations seeking to transform data into actionable business information. Through the use of standard interfaces, KnowledgeSERVER® also supports automated processes (such as refreshing scores and models), as well as delivering real-time scoring as part of predictive analytics solutions.

Key features of KnowledgeSERVER®:

  • supports computationally demanding predictive analytics on exceptionally large data sets
  • performs multiple concurrent operations on multiple data sets
  • provides analytics departments with support to work flow, task allocation and collaborative work environments
  • provides remote users with access to a centrally hosted server for activities
  • integrates with MS SQL Server to extend the capabilities of the MS SQL Server Analysis Services module
  • supports model deployment and scoring within an integrated IBM DB2 or Oracle-based data warehouses
  • can be integrated by organizations running BI platforms or OLAP servers for complementary data mining decision making
  • runs on Windows and Unix platforms

Model Management

Mining Manager® provides organizations using data mining with the ability to streamline and improve the management of predictive analytics workflows, modeling outputs and scores.

Key features of Mining Manager®:

  • thin-client environment
  • well-defined, roles based secure environment
  • central repository for storage and management of predictive analytics work flows
  • ability to meet and exceed internal and regulatory compliance requirements for storing, documenting and tracking modeling system activities and outputs
  • easy access to system results for permitted stakeholders
  • seamless integration with Angoss, SAS and other modeling tools


contact us For a more detailed review of your needs, or to request additional information.














 
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