What is the difference between a data analyst and a data scientist?

But there is still confusion about the differences between a data analyst and a data scientist, so we'll start our article:

What is the difference between a data analyst and a data scientist?
It is clear that both “data analyst” and “data scientist” have job descriptions related to data. But what is it?

A data analyst uses data to solve various problems and obtain actionable insights in the company. This is done by using different tools in specific data sets to answer companies' questions such as "Why is the marketing campaign more effective in certain areas?" Or "Why have product sales been reduced at present?" Etc., for this, the basic skills that a data analyst possesses are data mining, R, SQL, statistical analysis, data analysis, etc., and many data analysts can acquire the additional skills required to become data scientists.

A data scientist can design new processes and algorithms for modeling data, create predictive models, and perform custom analysis on data according to company requirements, so the main difference is that a data scientist can use complex software to design data modeling processes instead of using pre-existing processes to get answers from data like an analyst. Data, that's why the basic skills a data scientist possesses are Data Mining, R, SQL, Machine Learning, Hadoop, Statistical Analysis, Data Analysis, OOPS, etc.