Software

KXEN Event Log (KEL) compresses and combines transactions into a single data row to provide an efficient internal data representation, automating aggregation and transformation.

San Francisco, CA - June 25, 2001 - KXEN', a global analytic software company that provides powerful, predictive and descriptive data modeling technology for both data mining professionals and business decision-makers, today announced KEL (KXEN Event Log) as part of its analytics suite. KEL is a fast aggregation and transformation tool that enables analysts and business professionals to get more power out of their data warehouse.

Often, information to build predictive models is spread across multiple tables, one table containing customer reference data such as postal zip code, gender, social category, etc., and subsequent tables containing a log of events or transactions such as product purchase history, customer service call history, etc. KEL compresses and combines this information into a single data row to provide an efficient internal data representation. KEL automates this tedious data preparation process, allowing business practitioners to build predictive models and alter the attributes to make quick comparative results, without the need to involve IT professionals or savvy statisticians. KEL also enables users to run multiple event logs against each other to increase the degree of accuracy.

"KEL is an important addition to our core analytic offering," said J.D. de Haseth, president of KXEN. "This gives end users immense power so they do not have to depend on their strapped IT resources or cumbersome ETL tools to perform complex aggregation and data transformations. Now, KEL can run one or two passes on their data sets to quickly create a single record representation of a log of events in order to build predictive models more quickly. KEL complements our existing suite of analytic software that is fast, robust, easy to use, easy to integrate, and delivers results that are easy to interpret."

KEL aggregates and transforms transaction data, combines it with the customer or product level attributes, then feeds it into the additional regression and segmentation products of KXEN's analytic suite. KEL does not require any intermediate data storage or schema and can aggregate and pivot transformed transaction data sets using a unique reference date for each customer and product. For example, users could aggregate credit card purchases for any given customer during the first 12 months of their initial opening of an account to get a quick and easy read on account activity. KEL provides complete flexibility for users to select the aggregation period and intervals. For instance, users may decide to aggregate and transform credit card purchases for the first 12, 18, or 24 months since an account was opened; choose the first four, six, or eight quarters; or select three different six-month periods.

KXEN's full suite of patented software is easily integrated into applications and specific industry solutions, including customer relationship management, sales automation, supply chain management, network management, biotechnology, and financial. The KXEN suite automates the data preparation, coding, and modeling process and enables users to build predictive and descriptive models in near real-time for better business decisions.

For Pricing, Availability, and additional information please see www.kxen.com

Or Contact: Karen Higgins TMP Worldwide for KXEN Tel: (610) 251-6880 karen.higgins@tmp.com