Business Analysis - The Big Picture

There is lots of buzz in the market about analytics and that's the reason there are brurred lines for new comers to understand the overall scenario.
Today i am trying to draw a picture to cover the complete picture of the complete analytics business and related technologies. But before we dig deeper, let us define what is data analytics.

Definition of Data Analytics
The purpose of data analytics is to study at the data and find out the patterns in data. This could be further drilled down to the size of data we are looking at and type of patterns we need a output.
Usually the output of Data Analytics is a reports, because that is what business people understand.

Based on the findings we need we could divide the analytics majorly in the 4 categories. Based on the requirement of the business we could fit the requirement in any of the 4 categories.
But it is important to understand that there are not clear boundaries. Below picture explains complexity of the types and the value it brings in.

The first 2 type, Descriptive and Diagnostics are done after the event has happend. So we deal with the actual data of the business and tells the real picture. These 2 are mostly used together.

Descriptive analysis: What is happening
It is most common type of analytics and tell us what is happening. For e.g. it could tell us the monthly profit of the organisation for different demographic areas.
Effective visualizations are created to ensure right picture is visible to viewer.

Diagnostic Analysis: Why it is happening
After we know what is happening, it is important to understand the reasons. Use the diagnostic tools to drill down and isolate the root cause.

Comes next the more complex and valuable types of analytics Predictive and Prescriptive. This is forecasting of events based on the previous history and are mostly used together.
Predictive Analysis : What is likely to happen
Based of the previous data and predictive models, we forecast what is going to happen on a particular point of time. For eg. Every December the sales of retails companies increases.
As business world is full of uncertainties, it is always good to have certain information before hand. Which makes predictive analysis very powerful and valuable.

Prescriptive analysis : What to do 
This is most complex and valuable type of analysis. Here we tell the business that, based on th predictive analysis this is going to happen in this time frame and if we do this the opportunity could be maximized.
A day to day example would be Maps in our phone, which suggests us to take a different route when there is traffic on one route.

Will talk about different tools and models in a seperate post.