Data Science is one of the hot burning topic in the year 2020 but students and others often confuses between Data Analyst, Data Engineer and Data Scientist. This small post is about differentiating among these so that readers can choose their domains more effectively. This post is focused on skills required to become data analyst but also covers skills to become data engineer and scientist also.
| Data Analyst | Data Engineer | Data Scientist |
| Programming Language | Python|R|SaaS | Statistics and Probability |
| Tableau (Data Visualisation Tool) | Tableau & QlikView | Python | R | SaaS |
| QlikView (Data Visualisation Tool) | Data preparation Data Cleaning Data Wrangling | Data Modelling and creating algorithms for ML or DL problems |
| Excel | Pandas, Hadoop PySpark | Data Visualisation Tools |
Using the above table, it is clear that to become data analyst one must learn one of the programming language whereas data visualisation tools such as QlikView and Tableau are most needed and essential. Working on and practising excel will further add more skills to data analyst profession. In a nutshell, I would end the article with the below note
One must learn and implement specific skills to master the domain he/she wants.