The Predictive Model Markup Language (PMML) standard is developed by Data Mining Group (DMG), an independent consortium of over two dozen technology companies, including MicroStrategy.

The PMML standard describes how predictive models work and it makes the models to share across the organization for improved decision-making. This XML-based standard makes the integration of data mining models between MicroStrategy and other data mining applications possible.

MicroStrategy has said that data mining is an organic part of the company's architecture that enables users to discover hidden patterns and predictive information in the data through standard enterprise reports and dashboards.

While business intelligence (BI) provides deep insight into historical data, data mining uses this information to help companies forecast future events. With MicroStrategy, users can deploy complex data mining models and include the results of these models in a variety of BI applications, such as call center analyses, customer relationship management, and financial budgeting and forecasting.

An active member of DMG since 2004, MicroStrategy has provided guidance to set the PMML standard and continues to maintain its support for open platform standards, cross-vendor interoperability, and high data integrity.

Along with existing data mining models, MicroStrategy 9 includes new capabilities, such as the Time Series model, which is used to forecast results along a given timeline, and the Association Rules model, which is helpful for discovering relationships in databases and recommending products that customers are likely to purchase, MicroStrategy added.

Sanju Bansal, COO of MicroStrategy, said: "MicroStrategy is committed to innovations in advanced analytics for our customers, and we are pleased to have been actively involved in defining the standards for the release of PMML 4.0 and to be the first BI platform vendor to support it. Through our support of open standards like PMML, MicroStrategy provides its customers with the flexibility to deploy advanced analytics throughout the enterprise to gain valuable insight into key business areas, including customer segmentation, sales forecasts, churn analysis, and market-basket analysis."

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