Question

There are 4 categories of data analytics discussed in Chapter 7 reading: descriptive, diagnotisc, predictive, and prescriptive. Select one and explain. Give examples.

Answer 1

WHAT - DESCRIPTIVE

WHY - DIAGNOSTIC

IF - PREDICTIVE

HOW - PRESCRIPTIVE

1. Prescriptive – This type of analysis reveals what actions should be taken. This is the most valuable kind of analysis and usually results in rules and recommendations for next steps.
2. Predictive – An analysis of likely scenarios of what might happen. The deliverables are usually a predictive forecast.
3. Diagnostic – A look at past performance to determine what happened and why. The result of the analysis is often an analytic dashboard.
4. Descriptive – What is happening now based on incoming data. To mine the analytics, you typically use a real-time dashboard and/or email reports.

Predictive Analysis :- The subsequent step in data reduction is predictive analytics. Predictive analytics use big data to identify past patterns to predict the future. However, it is important to note that it cannot predict if an event will occur in the future; it merely forecasts what are the probabilities of the occurrence of the event. A predictive model builds on the preliminary descriptive analytics stage to derive the possibility of the outcomes.

Dr. Michael Wu, chief scientist of San Francisco-based Lithium Technologies said -"The purpose of predictive analytics is NOT to tell you what will happen in the future. It cannot do that. In fact, no analytics can do that. Predictive analytics can only forecast what might happen in the future, because all predictive analytics are probabilistic in nature."

For example, some companies are using predictive analytics for sales lead scoring. Some companies have gone one step further use predictive analytics for the entire sales process, analyzing lead source, number of communications, types of communications, social media, documents, CRM data, etc.