[News - Viscovery]
Viscovery's visual workbench extends data mining to business users
Vienna / Austria, July 2008 - Viscovery Software GmbH, a leading provider of data mining and predictive analytics solutions, has been positioned by Gartner, Inc. in the Magic Quadrant for Customer Data-Mining Applications1. In the report, international data mining vendors were evaluated based on their completeness of vision and ability to execute. In particular the companies' products and services were evaluated, as well as their market responsiveness and track records. Gartner's Magic Quadrant 2008 for Customer Data-Mining Applications includes eight companies worldwide.
"We believe our listing in the Magic Quadrant by Gartner confirms our ability to deliver proven predictive analytics solutions that help our clients easily and quickly evaluate their data and predict future customer behavior," said Gerhard Kranner, CEO of Viscovery Software GmbH. "With the recent launch of version 5 of the Viscovery line of products, we have taken a step further in our mission to make our intuitive visual data mining solution a strategic instrument for a wide range of users."
Intuitive predictive modeling and scoring accuracy set Viscovery apart
The Viscovery suite for visual data mining and predictive analytics covers all functions needed for customer analytics projects - from clustering, customer profiling and segmentation, through scoring and non-linear prediction, up to automatic generation and real-time integration of models. The interactive project environment supports effective model management and contains standard workflows with default parameterizations, which allow simple click-through usage and can be re-used as process patterns.
The robust, high-performance software combines statistical methods with Self-Organizing Maps (SOMs), which allows huge quantities of data to be visualized and handled on a single screen. This intuitive visual approach enables even statistics laymen to explore complex data, recognize relationships, create scoring models and define target groups. Models can be easily deployed in real-time applications and flexibly integrated in verticals for specific application areas.