KXEN Unveils Analytical Data Management and Modeling Factory – Supercharging Agility and Productivity in Predictive Analytics

KXEN introduces predictive analytics’ first semantic layer, eliminating time-consuming processes by scheduling automatic updates of analytical data sets and models.

KXEN, the data mining automation company, today announced the next chapter in predictive analytics with its Analytical Data Management (ADM) and Modeling Factory (KMF). This introduces predictive analytics’ first-ever 'semantic layer' combined with powerful scheduling capabilities to provide orders of magnitude increases in agility and productivity to deal with today’s business challenges.

For over 10 years, KXEN has brought next-generation predictive analytics to more than 400 of the world’s leading companies including Bank of America, Barclays, Cox Communications, Lowe’s, Meredith Corporation, Overstock.com, Rogers, Vodafone, and Wells Fargo.  Powered by KXEN’s patented data mining automation capabilities, customers have cut the time it takes to build complex analytical models from months to days.

Today’s business environment is becoming increasingly complex as the cloud changes the nature of customer relationships.  Companies are trying to take advantage of new sources of personalised data and customers are demanding customised interactions in real-time.  Unfortunately, traditional predictive analytic tools and technologies require months to build the underlying models needed to create complex offers, decisions and policies.

The launch of KXEN’s Analytical Data Management and Modeling Factory allow businesses to supercharge their predictive analytic processes with increasingly intelligent models built in only hours.

KXEN Analytical Data Management (ADM) – predictive modeling’s first semantic layer

Similar to the breakthrough of a semantic layer made by business intelligence solutions to solve skyrocketing demand in reporting, KXEN is introducing predictive modeling’s first ever semantic layer, a reusable and easily modifiable analytical record comprised of business relationships or data domains and fields.  With the introduction of Analytical Data Management, KXEN will enable companies to:

- Create a reusable analytical record (semantic layer): Allowing power users to assemble valuable customer data once to provide the framework to build unlimited analytical data sets and models.
- Build self-service models: Putting the power of complex modeling at the hands of the business.  Business users will be able to build models on demand replacing the slow, manual process required by traditional data mining technologies.
- Reduce human error: The combination of the analytical record and KXEN’s modeling automation dramatically reduces the chance of human error and automatically creates an institutional memory for complex processes that are rarely documented and not easily maintained.

KXEN Modeling Factory (KMF) – automatic refresh of analytical data sets and models

With clicks and not code, business users can schedule model refreshes to make sure that customer interactions and decisions are based on the latest information. With Modeling Factory, businesses will be able to:

- Schedule model updates: Business users can setup recurring or one-time model refreshes with clicks not code.  Eliminating the need for power users to manage these time intensive processes allows the business to scale.
- Recreates analytical data sets:  Leveraging the Analytical Data Management technology, analytical data sets are automatically recreated from the semantic layer eliminating manual efforts that previously took days. 
- Deploys Scores to Production Systems: Resulting scoring equations are deployed in-database to the data warehouse or directly into transactional systems like CRM solutions and call centre technologies.
- Alerts users of data deviations: Automatic notifications allow users to manage by exception any patterns that may impact business results.

Comments on the News
“KXEN continues to revolutionise the predictive analytics market. Our modeling automation allowed organisations to produce optimised models in days not months. Now, businesses can model at a much more detailed level for every customer interaction, making it easier than ever to make the right offer at the right time to the right customer,” said John Ball, CEO of KXEN.

“One of the main challenges facing Neopost was the laborious task of data analysis and processing, involving the extraction, segmentation and analysis of data from its business applications.  With KXEN’s Analytical Data Management module, we are able to automatically generate analytical data sets, making the modeling process easier and faster,” said Thanassis Thomopoulos, Head of Strategy and CRM at Neopost France.

“The automated generation of risk scores is controlled by the combination of KXEN's Analytical Data Management and Modeling Factory solutions. With these in place, we’ve boosted productivity and optimised critical business processes,” said Thomas Piton, Data Miner at VM Matériaux.

“KXEN tests the limits of modern predictive analytics by helping to eliminate many of the bottlenecks impacting the effectiveness and efficiency of data mining solutions.  By applying a semantic layer to modeling, KXEN is able to dynamically refresh analytical data sets directly from the Teradata data warehouse and deploy analytic equations in-database to leverage the power and performance of the Teradata platform,” said Stephen Brobst, CTO at Teradata Corporation.

“KXEN focuses on expanding the use of [predictive analytics/data mining] within analyst communities, making them more productive and more responsive to business needs, as well as among business consultants with no particular knowledge of statistics,” wrote James Kobielus in the independent Forrester Research, Inc. report, The Forrester Wave: Predictive Analytics And Data Mining, Q1 2010 (February 2010).