ECONOMICS

Detailed explanation-1: -At their best, prescriptive analytics predict not only what will happen, but also why it will happen, providing recommendations regarding actions that will take advantage of the predictions. These analytics go beyond descriptive and predictive analytics by recommending one or more possible courses of action.

Detailed explanation-2: -Prescriptive analytics answers the question “What should/can be done?” by using machine learning, modeling, simulation, heuristics, and other methods to predict outcomes and provide decision options.

Detailed explanation-3: -Prescriptive questions: These are questions that ask what we should do about a particular development challenge. “What intervention would be most appropriate in this context for increasing grade level 3 child literacy rates?” is and example of a prescriptive question.

Detailed explanation-4: -Prescriptive analytics has been called “the future of data analytics, ” and for good reason. This type of analysis goes beyond explanations and predictions to recommend the best course of action moving forward. It’s especially useful in driving data-informed decision-making.

Detailed explanation-5: -Here are some common examples of prescriptive analytics and types of prescriptive insights provided by advanced data analytics tools. Reduce risk by automatically analyzing credit risk or loan default likelihood. Provide better patient care based on patient admission and readmission forecasting.