KMF Department - Analytical CRM, data mining application, social network analysis software

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KMF DEPARTMENT

KXEN Modeling Factory (KMF) has been designed to automate the development and maintenance of predictive analytics-intensive systems, especially systems that include large numbers of models, vast amounts of data or require frequent model refreshes. Information about each project and model is monitored and disseminated to ensure complete management and oversight and to facilitate continual improvement in business performance.

At KXEN, we believe that tasks that can be automated should be. But we recognize that automated systems must provide transparency and alerting mechanisms to quickly focus analysts and business stakeholders on potential problems or opportunities. We also believe that skilled analysts are becoming more scarce and as such, you should allow them to spend more of their time on the interesting work that requires their art and skills, rather than tedious repetitive tasks.

Main Functions

Schedule: creation of the Analytic Data Set (ADS), setup of how and when to score, setup of when and how to perform model retraining and refreshes ...

Report: Monitormodel execution over time, Track changes in model quality over time, see how useful one variable is by considering its multiple instance in models ...

Notification: Rather than having to wade through pages of event logs, KMF Department allows users to manage by exception through notifications.

Key Benefits

Refresh More Frequently: Predictive modeling should never be a one-shot process. Direct marketers can improve the predictive performance of models by continually incorporating the results from their most recent direct marketing campaign and response activity. There are several reasons why model updates lead to better marketing results.

Manage by Exception: There is no need to dedicate a full team to managing the process. Only a few people are required, since KMF Department allows "management by exception." KMF supports this by allowing users to subscribe to structured events. Users receive e-mail notifications when something occurs that interests them.

Simple GUI: Automation has always been the key driver of KXEN strategic development and is still the cornerstone of KMF Department. A graphical interface easily guides users through a repeatable process for building and registering models for testing and validation. The ease of use and automation capabilities makes it possible to develop many more models with the same resources.

Prevent Human Error: KMF Department reduces costs related to risks and errors of operational predictive analytics projects by automating processes that need not require human intervention while also warning subscribed users of any critical issue.

KMF Department Proves Accountability for the Business: Analytical managers receive comprehensive reports on things like data usage, modeling servers and project status. Reports also show profitability with respect to resource usage.
Respond to Market Changes: Success during rapid economic changes requires businesses to be able to make changes immediately. A time lag can be extremely costly. KMF Department improves agility and time-to-market, by providing easy changes to scheduling (for example from every month to every week) in just a few clicks organizations can detect exactly when their environments start to change so that they respond more quickly.

Repeatable Dataset Creation: A key capability is the support of analytical dataset creation and lifecycle. Rather than having to redefine a new dataset each time a new model needs to be built, KXEN Analytical Data Management (ADM) automates this analytical dataset creation and versioning.

By managing administration rights: KXEN Modeling Factory Department makes work easier and faster for IT Staff. Through an intuitive and easy-to-use Web user interface, KXEN Modeling Factory provides decentralized, distributed and simplified administration of users rights and permissions. The result is a secure delegation of administration activities.

Download the KMF Department overview brochure

Structural Risk Minimization (SRM)

The primary challenge for statisticians has been to build highly accurate models that are also reliable. This has been particularly difficult given the large number of variables in computer-generated data. Traditional statistics can only produce an accurate model with a few variables, so an expert is needed to reduce the number of variables before building a model. The more variables there are, the more difficult it is to build a reliable model. Only the expertise of the statistician determines the reliability of the model.

SRM, developed by Vladimir Vapnik, is a breakthrough in mathematics and statistics that for the first time makes it possible to automatically build reliable and accurate models. In contrast to traditional statistical models, SRM models become more accurate and are still reliable as the number of variables is increased. Model Accuracy and Reliability are determined by the data, not by the expert.