Predictive and prescriptive analysis in Data science for analyst.
Both predictive and prescriptive analytics is a BI tool to analyze the data and their behavior to make predictions and take the decision, we make the prediction based on the past and present dataset that we have, and then it will take care by prescriptive analysis to take suitable action for the business. The predictive analysis comes after the descriptive analysis that is to collect the information from the data about what happened in the past?
The main aim of these two analytical methods is to get out the meaningful insights from the data and after predicting the result the action will be taken to improve the business operations. Four analytical methods used in business analysis are Drescripive, Digontive, Prescriptive, and Predictive.
Here You will get to know about the Predictive and prescriptive analysis in data science:
What is Predictive analysis?
The predictive analysis is probabilistic as the main purpose of the predictive analytics that It doesn’t tell about what will be happening in the future it only provides you a forecast that what might happen to be future, even nobody can make the guarantee that this is going to happen in future.
The predictive analytics contains three key that is decision analysis, predicting modeling, and optimization. Predictive analysis helps to identify the risks and opportunities that can be done by recognizing the pattern that can occur the causes.
Predictive analysis is a method to predict the outcomes when the historical data feeds into a Machine learning model that considers key points and Patterns and then the present data is feed into the machine learning to predict what will happen next.
For example, consider a supermart is implementing predictive analytics that identifies that a customer named Alice will most likely buy what they need so if supermart offers something that they will like to buy or not it will be based on the historical data. If Alice goes to the supermart next time she may buy that product, This is about predictive analysis for the real-time scenario.
What is Prescriptive Analytics?
The prescriptive analysis is another BI tool that takes the predictive analysis one step further to solve the problem which is found out after predicting the model, it is a decision-making method. It offers actionable steps for solving a problem.
It solves the problem such as what will happen in the future, how it will happen, and why it will happen that told by the predictive analysis.
It is also done with the Machine learning model that will suggest many options to get the benefit and mitigate future risks.
Prescriptive Analytics allows both types of datasets such as structured( categorical and numerical values)and unstructured (image, text, audio, and video). It is an AI-powered technique to build business rules. It is a decision making analytical tool and the decision based on the problem that is identified by the result that predictive analysis given.
How AI uses prescriptive analytics:
The model takes new data and produces more accurate outcomes and many decision options, Machine learning model applied on the data and processing it with a neural network that makes machine learn efficiently about the data to make appropriate results
As Mentioned above the example of the supermart We predict that the customer will buy the product or not? And prescriptive analytics that gives the offer of a product or on a product so that customers will buy the product.
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