Data Analysis and Interpretation

This blog will differentiate Data Analysis and Data Interpretation.
Data analysis is making a summary of gathered data. This is what a Data Scientist does.
Data Interpretation is extracting the meaningful information out of the summarized Data. After research Data Scientist does this too.
Data analysis starts just after collecting the data. The data is divided into analytical units, modules based on patterns. For Example “A class teacher maintains a register of attendance for two classes. At the end of the month she finds out the worst offenders. She divides the data into two sets first. Class A and Class B. The two sets become two separate analytical units which are then analyzed separately. Further she divides each set into different modules based on patterns such as a student remains absent every Tuesday. She then calls student’s parents to ask for his/her absence on a particular day every week.”
So this is the traditional way of managing and making summary of the data. So In the above example, Teacher collects data of two classes for the whole month then she analyzes it before interpreting it to the offender’s parents.
This way of managing the data is manual which can be automated as per the requirements using several coding techniques like VBA, VB.NET, Java etc.
So the 4 basic steps of processing Data are concluded as follows :  -
1.) Collecting Data (Surveys, Reports, Gather etc etc)
2.) Analyzing Data (Analyzing Causes. effects and Consequences)
3.) Summarizing Data (Bringing Data into Readable Format)
4.) Interpreting Data (Displaying Findings & Stating what’s missing)
My Next Blog will focus on Qualitative vs Quantitative Research.