You know the saying "an ounce of prevention is worth a pound of cure." From the state department of revenue to the regional water authority, the need for preventive measures is becoming a key driver of predictive analytics' rapid growth in the public sector.
How does predictive analytics support the premise of prevention, and what do we really mean by prevention as it applies to predictive analytics? In this case, prevention simply means identifying a problem from data or noticing the inclination for a problem before it grows into a much larger issue. Based on a series of proven algorithms, these what-if scenarios provide the user with insight into future probabilities and trends.
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