{"id":50428,"date":"2019-02-25T10:15:17","date_gmt":"2019-02-25T04:45:17","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=50428"},"modified":"2025-07-31T21:33:56","modified_gmt":"2025-07-31T16:03:56","slug":"data-science-vs-data-analytics-infographic","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/data-science-vs-data-analytics-infographic\/","title":{"rendered":"Data Science vs Data Analytics Infographic – Choose Your Career"},"content":{"rendered":"

As we further ourselves technologically, there are times when a new technology comes in and changes the whole picture. Big Data<\/strong><\/a> is visibly the trend for the 21st century as we continue to best ourselves in the amount of data we generate every year.<\/p>\n

For those working in the IT industry, the terms “Data Science” and “Data Analytics” appear both- lucrative and exciting. However similar they may sound, they explain mildly different disciplines.<\/p>\n

To clear the air, we have curated this Data Science Vs Data Analytics infographic<\/strong> for you so you no longer confuse the two.<\/p>\n

This can be of help to you whether you’re a fresher looking to build a career, an employee with a mid-career crisis, or a data scientist or analyst yourself. Read on to find out how the two are different, and which one is the right pick for you.<\/p>\n

Data Science vs Data Analytics Infographic<\/h3>\n

\"Difference<\/a><\/p>\n

Data Science<\/strong><\/a> is a field that makes use of scientific methods and algorithms in order to extract knowledge and discover insights from data (structured on unstructured).<\/p>\n

Data Analytics is the process of using specialized systems and software to inspect information in datasets in order to derive conclusions. This focuses on specific areas with specific goals. Briefly, the two perform the following roles:<\/p>\n

Data Scientist:<\/p>\n