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iii. Prescriptive Analytics

Prescriptive analytics entails data analysis to offer suggestions on

what steps should be performed to obtain a specific result (Rawat,

2021). It assists in determining the appropriate course of action to
pursue in light of the information at hand. Prescriptive analytics, for

instance, can be used to suggest the ideal marketing plan for a specific

product based on consumer behaviour and preferences.

In order to provide suggestions, prescriptive analytics often needs to
combine historical data, real-time data, business rules, and

limitations. In order to determine the optimum course of action based
on set objectives and optimisation criteria, it takes into account a

variety of scenarios, limitations, and trade-offs.

iv. Prediction Analytics

According to Riahi (2018), prediction analytics is the process of

analysing data to forecast future occurrences or patterns. It assists in
finding patterns and trends in data so that future results can be

predicted. Predictive analytics, for instance, can be used to forecast
future sales of a specific product based on historical sales data and

industry patterns.

Predictive analytics employs a variety of methodologies, including

regression analysis, time series forecasting, data mining, and machine
learning algorithms. Researcher can use these techniques to find

patterns, dependencies, and linkages in the data that can be utilised to

generate precise forecasts.

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