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.

Comparison Table

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


data analytics

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.