ANSWER

There are three main types of data analytics, with increasing levels of complexity. The value of each type is relevant to the nature of the business problem to be solved. Each type of analysis offers different information and insights to address different business needs.

• Descriptive analytics: uses historical data to understand and analyze past business performance. This type of analysis is useful in understanding the business strengths and weaknesses, and building an understanding of the customer-base. Online retail sites use descriptive analytics in order to make product suggestions (“customers who like x also like…”), for example
• Predictive analytics: applies statistical analysis methods against historical data to identify patterns, and then uses that understanding of relationships and trends to make predictions about future events based on probabilities. Predictive analysis does not produce a single definitive future-state, but offers a range of possible future-states and the likelihood of each. It does not tell what ‘will’ happen, but only what ‘could’ happen. Insurance companies use predictive analytics to determine probability of motor vehicle claims based on age, gender, geographic location, etc. – and the premiums charged to each customer are then based on these predictive models.
• Prescriptive analytics: expands on predictive analytics to identify decisions to be made, and identify likely outcomes of each decision or course of action. Prescriptive analytics builds upon predictive analysis, to make recommendations intended to increase the probability of a desired future-state outcome. Prescriptive analytics can be used in supply-chain operations to manage inventory and schedule product shipments according to sales forecast predictions, to better align the allocation of materials against projected demand.

Here is a 3 min video describing the 3 Types of Data Analytics