SEATTLE February 19, 2002 Analytics is the name of the game in data software these days and Insightful Corporation, an enterprise software solutions company for data analysis, is making predictive analysis its new holy grail. Toward this goal, the company today announced Insightful Miner Desktop Edition, a new, scalable data mining software solution.
Insightful Miner is essentially a big-data workbench for building predictive analysis applications. It is designed for new data miners and skilled analysts who need integrated support for the entire data mining process including data access, manipulation, cleaning, model building, evaluation and deployment. Users interact with large data sets with unprecedented ease and efficiency. Powerful data cleaning capabilities improve the accuracy of predictive models for better estimates and smarter decision-making.
"Insightful Miner is a comprehensive, full life-cycle data mining workbench," said Greg James, vice president of National City Corporation. "It combines the power and flexibility of the S-PLUS statistics language and world-class, interactive data exploration techniques, all within an intuitive, user-friendly environment. Visually exploring large, multi-dimensional data sets and evaluating predictive models is incredibly fast and easy. Researchers and practitioners alike will immediately appreciate this new data mining tool.
"As the amount of data collected increases, so will the competitive pressure to extract value from it," said Shawn Javid, president, CEO and chairman of Insightful. "Data mining and predictive analysis are critical for business intelligence, yet existing solutions are either incomplete, inflexible or too expensive. Pre-packaged analytic applications are often a poor fit. Our decade of research in high-end analytics confirms that data mining and predictive modeling are areas of business intelligence that require a well-tailored analytic solution to produce information superiority and a clear ROI."
Initial responses from Insightful's early adopter program confirm that the visual workflow environment and data mining components break down the learning barriers to data mining. Advanced visualization tools using Trellis graphics make it easy to detect and understand the patterns, trends and relationships in high-dimension data.
