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Predictive analytics encompasses a variety of statistical techniques from predictive modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events. Essentially a collection of many algorithms and techniques, the goal is to teach computers to make and improve predictions based on the data available.
The defining element of this approach is that predictive analytics provides a predictive score (probability) for each individual outcome and determines actions that can be taken to influence performance.
Generally, the predictive abilities of a system for building-specific behaviors increases with time. By extension, trained datasets based on highly granular equipment level datastreams facilitates onboarding, as performance anomalies are identified right away.
When applied to real estate operations and management, predictive analytics produce the ability to interpret and react to data that has never been seen before, which is a core requirement for processing vast amounts of data from equipment that is similar, but not identical.Back to FAQ