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What exactly Prescriptive Analytics is?
Prescriptive analytics is a statistical method used to generate recommendations and help in decision making based on the computational findings of algorithmic models. It focuses on finding the best course of action in a situation based on the available data. Prescriptive Analytics is related to descriptive analytics as well as predictive analytics but helps in understanding actionable insights instead of just monitoring the data.
Descriptive analytics offers valuable insights into what has happened, whereas predictive analytics helps to forecast possible outcomes. Prescriptive analytics on the other hand, factors information about possible situations or scenarios, available resources, past performance, and current performance, and suggests best possible course of action or strategy. It not only anticipates what will happen and when it will happen, but also why it will happen. Also, prescriptive analytics provides decision options to take advantage of a future opportunity or mitigate a future risk.
How Prescriptive Analytics works?
Prescriptive analytics processes business rules along with the structured data (such as numbers, categories etc.) as well as unstructured data (such as texts, images, sounds, videos, etc.). It uses various artificial intelligence techniques such as machine learning, natural language processing, computer vision, pattern recognition, image processing, speech recognition, and signal processing to predict what lies ahead and to prescribe how to take advantage of this predicted future limiting risks. It can help prevent losses, limit risk, increase efficiency and meet business goals. However, it can only be effective if businesses know what questions to ask and how to react to the answers. If the input rules are accurate, the output results will be incorrect.
Applying Prescriptive Analytics to Healthcare Sector
Prescriptive analytics software that uses machine learning, Decision Tree, Support Vector Machine (SVM) can be used to improve efficiency of doctors to diagnose patients of diseases accurately and in an economical way. It can also reduce time taken to analyse numerous variables to potentially improve upon/ assist doctor’s diagnosis.
Category: Analytics, Artificial Intelligence, Big Data and BI