Data Types and their usage in Analytics

Data is everywhere, and most companies nowadays captures data from different touch points. On the other hand, understanding captured data to influence decision making is still a skill to be mastered by most of the businesses.

Data analysis in a major pillar in any Digital Transformation Journey that businesses should be focusing more and more on in this competitive and challenging times.

Retail Consumer data, for example, help analyze customer’s purchasing behavior and what influences their decisions. By understanding better wow clients’ decision where made, businesses can remodel and enhance their offerings to increase revenue.

Below are four different types of data used in Analytics:     

1- Descriptive Data: (What is happening?)       

Describes what is happening now based on real time incoming data. This is fast Data and works to deliver information in real time, with accurate results. Surveillance cameras, for example, provides this kind of data to the police to take immediate actions.

2-Diagnostic Data: (Why it is happening?)       

Are records of what and why things have happened. This kind of data is usually automatically recorded and is extremely valuable to identify the causes and diagnose them. Used, for example, in airplane black box, or even in PCs and Mobile to enhance products.

3-Predictive Data: (What is likely to happen in the future?)    

The most and commonly used Big data type that analyze what might happen based on previous trends and patterns. Companies analyze this kind of data to find patterns that would help them “predict” the future and take decisions.     

4-Prescriptive Data: (What do you need to do?)

Shows and clarifies what is next to be done based on current data to bypass or eliminate future issues.

Victor Abou Rahal