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 |
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.
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