Predictive analytics

Predictive analytics, or predictive AI, encompasses a variety of <a href="/facts/Statistics/DNPsKGYU">statistical</a> techniques from <a href="/facts/Data_mining/AH53q5ac">data mining</a>, <a href="/facts/Predictive_modelling/VI5ThSKa">predictive modeling</a>, and <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a> that analyze current and historical facts to make <a href="/facts/Prediction/0w4XXB33">predictions</a> about future or otherwise unknown events.
In business, predictive models exploit <a href="/facts/Pattern_detection/o1s38opj">patterns</a> found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding <a href="/facts/Decision-making/NbJYprSw">decision-making</a> for candidate transactions.
The defining functional effect of these technical approaches is that <a href="https://www.galaxyweblinks.com/blog/predictive-analytics-inventory-management">predictive analytics provides a predictive score</a> (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detection, manufacturing, healthcare, and government operations including law enforcement.

Predictive analytics open-in-new

Predictive analytics