Nov 03, 2022

37: Data Science vs Data Analytics — How to decide which one is right for you?

Data Analyst and Data Scientist are two prominent examples where many people believe that a data scientist is just a reclassified analyst specifically dealing with data.

Data analysts and data scientists focus on similar subject areas, but they go about these in slightly different ways.

Data science is the process of extracting knowledge and discovering patterns from data. It is similar to data analytics but with a different focus. Data science is more focused on the “why” while data analytics focuses on the “what.”

Data analysts are responsible for analyzing raw data to find trends or patterns and then present their findings in a way that makes it easy for people to understand. They use statistical methods, data mining, and other tools to extract information from large datasets.

Watch and join our hosts @samanthabretous & @phoenix to comprehend the differences between Data Analyst and Data Science. Even learn about a new role called Analytics Engineering!


  • 0:00 – 0:41 Intro
  • 0:46 – 2:32 What’s The Difference Between A Data Analyst And A Data Scientist?
  • 2:32 – 2:50 Is Data Scientist More Popular Than Data Analyst?
  • 2:51 – 3:14 Is Becoming a Data Scientist or Data Analyst Easier To Get Into?
  • 3:18 – 4:13 What Skills Are Required As A Data Scientist?
  • 4:13 – 4:58 What Skills Are Required As A Data Analyst?
  • 5:05 – 7:18 What’s The Frontend And Backend Like In Data Analyst Engineering?
  • 7:19 – 7:37 Who Is The Analytics Engineering’s Stakeholder?
  • 7:50 – 9:52 How Do Data Analyst Process Data?
  • 9:52 – 11:22 What Made You Choose This Route?
  • 11:24 – 11:54 What To Look For In An Analytics Engineering Role?
  • 11:55 – 12:24 How Would You Define The Data Field?
  • 12:25 – 12:38 – Closing Remarks

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37: Data Science vs Data Analytics — How to decide which one is right for you?


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