In today’s data-driven world, most business decisions are backed/informed by data insights. There are many terminologies related to the digital industry that might have people confused. In this blog post, I hope to bring some clarity to everyone about the difference between 2 terms: Data Analysis and Data Analytics.
I found that the fastest way to help people distinguish two concepts is to put them all into a comparison table.
|Factors||Data Analysis||Data Analytics|
|Input||Raw data||Usually, clean data has gone through a transformation process from the raw sources|
|Output||Some statistics pointed out from the data (e.g. the percentage of failed deliveries, the total amount of sales value in a month)||Some insights that can inform business decisions (e.g. sales trend over 2 years which help to forecast sales of next year)|
|Main activities||Data collection, Data evaluation||Data collection, Data evaluation, Data transformation, Data modeling, Data visualization, Data interpretation, Data Learning|
Relationship between Data Analysis & Data Analytics
In short, Data Analysis is a subset of Data Analytics. Besides data analysis, Data Analytics also requires expertise in other majors of data modeling, data patterns, machine learning models, etc.