With all the definitions of data analysis in our previous post, exploring into data analysis types to further our knowledge into data analysis.
With the huge attention on data, collection is just the tip of the iceberg, we need to focus on analyzing the data. Let's find out on the 1st type of data analysis
Descriptive Analysis (What is happening?)
It is the simplest and most common use of data in business today. This type of analysis could be used to understand customer demographics and categorize them into data buckets (i.e. youth, self employed, retirees, fresh grads, seniors etc).
The main purpose of the analysis is to "describe something".
Examples of descriptive analysis are :
Times that customers view website
How well sales team is performing for Q1
Assessing credit risk
Categorize customer profile for preferred services or products
From a business application perspective, the direct application of descriptive analysis is identified as Key Performance Indicators which are indicators to describe how successful they are in their job role. This is the main reason why KPIs are utilised in performance review so that supervisors/managers can have a description of how well the employee has been doing well in the job role.
Descriptive Analysis can be present in a web and online based analytics that provides a description of how well something is doing, such as :
- Google analytics
- Website analytics
- Facebook analytics
- Email analytics
These applications give the users a sense or an idea of how the online application is adding or subtracting value. The simplest step to descriptive analysis would be to use the above mentioned applications and figure out what are the indicators and what it could mean
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