Types of Analytics
Analytics is used in almost every industry. The technological changes you see every day is all because of analytics. Today we will see the main types of analytics
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
Let’s discuss analytics types as follows.
Descriptive Analytics :
Descriptive analytics deals with past trends data, it basically finds out what has happened in the past, and based on past data or historic data it predicts the future outcome. One of the main objectives of descriptive analytics is to look at the trends of past data, summarize it in an innovative way that can be useful for generating insight.
Let’s take an example of DMart, we can look at the product’s history and find out which products have been sold more or which products have large demand by looking at the product sold trends and based on their analysis we can further make the decision of putting a stock of that item in large quantity for the coming year.
Diagnostic Analytics :
Diagnostic analysis works hand in hand with Descriptive analytics. As descriptive analytics find out what happened in the past, diagnostic analytics, on the other hand, finds out why did that happen or what measures were taken at that time, or how frequent it has happened.it basically gives a detailed explanation of a particular scenario by understanding behavior patterns.
Let’s take the example of Dmart again. Now if we want to find out why a particular product has a lot of demand, is it because of their brand or is it because of quality. All this information can easily be identified using diagnostic analytics.
Predictive Analytics :
Whatever information we have received from descriptive and diagnostic analytics, we can use that information to predict future data. it basically finds out what is likely to happen in the future. Now when I say future data doesn’t mean we have become fortune-tellers, by looking at the past trends and behavioral patterns we are forecasting that it might happen in the future.
The best example would be Amazon and Netflix recommender system. You might have noticed that whenever you buy any product from Amazon, on the payment side it shows you a recommendation saying the customer who purchased this has also purchased this product that recommendation is based on the customer purchased behavior in the past. By looking at customer past purchase behavior analyst creates an association between each product and that’s the reason it shows recommendation when you buy any product.
The next example would be Netflix, when you watch any movies or web series on Netflix you can see that Netflix provide you with a lot of recommended movies or web series, that recommendation is based on past data or past trends, it identifies which movie or series has gain lot of public interest and based on that it creates a recommendation
Prescriptive Analytics :
This is an advanced method of Predictive analytics. Now when you predict something or when you start thinking out of the box you will definitely have a lot of options, and then we get confused as to which option will actually work. Prescriptive analytics helps to find which is the best option to make it happen or work. As predictive analytics forecast future data, Prescriptive analytics on the other hand helps to make it happen whatever we have forecasted. Prescriptive analytics is the highest level of analytics that is used for choosing the best optimal solution by looking at descriptive, diagnostic, and predictive data.
The best example would be Google self-driving Car, by looking at the past trends and forecasted data it identifies when to turn or when to slow down, works much like a human driver.