Predictive analytics models: These models focus on answering the question, “What will happen?” Predictive analytics involves the process of utilizing data to forecast future trends and events. Predictive analysis can either be carried out manually, commonly referred to as analyst-driven predictive analytics, or through the utilization of machine learning algorithms, also known as data-driven predictive analytics. In either case, historical data serves as the basis for making future predictions.
Prescriptive analytics models: These models assist in netherlands whatsapp number data answering the question, “How can we make it happen?” Essentially, prescriptive analytics recommends the optimal course of action for progression, utilizing optimization and simulation techniques. Typically, predictive analysis and prescriptive analytics are intertwined, as predictive analytics identifies potential outcomes while prescriptive analytics explores these outcomes and identifies further options.
Another perspective on analytics models is based on the level of uncertainty or probability associated with deriving insights analytics models:
Deterministic models: These models provide insights accurately with certainty. Typically, insights derived from historical data fall into this category.
Stochastic models: These models incorporate randomness or uncertainty into the model. Insights regarding future states derived from Regression and Gradient Boosting Machines (GBM) models exhibit a level of uncertainty and are considered stochastic.