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KXEN, An SAP Company

Prepare Your Data



Modeling’s First-Ever Semantic Layer

Before you can build a predictive model, you have to prepare and transform your data into a format that analytical engines can process. Unfortunately, this step traditionally takes upwards of 40% to 50% of the time spent on any predictive analytics project. To make matters worse, it has to be done each and every time you want to create a predictive model.

To eliminate this bottleneck, KXEN introduced predictive analytics’ first-ever semantic layer. It’s called InfiniteInsight® Explorer, and it’s similar to the semantic layer introduced in the early 90’s by business intelligence companies to unblock the reporting bottleneck.

In a nutshell, power users define a broad set of reusable business components, called analytical records, which can be applied over and over again to automatically create the analytical data sets used for modeling. This innovative approach is orders of magnitude faster and results in far less human error than traditional handcrafted techniques.

It also opens the door for business users to self-service their predictive modeling needs, while guaranteeing accurate results.

  • Build reusable analytical records used to create unlimited analytical data sets
  • Describe the thousands of attributes that comprise your domains of interest
  • One-time definition of aggregates and  attributes with time dependencies
  • Transforms textual fields into root word coding
  • Builds social graph from actual customer interactions
  • Optimized encoding for classification, regression, clustering, forecasting, etc.
  • Optimized for major database platforms (SAP HANA, Teradata, Oracle, Microsoft SQL Server, IBM DB2, Netezza, etc.)

The time spent to construct derived variables and transformations has been greatly reduced with InfiniteInsight®. 

Richard Wherry, SVP Market Information Manager, GWIM Client Analytics & Modeling

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