- Unlike in academic environment, business data are mostly stored in relational databases. It is economical and secure to perform data analytics/data science jobs within databases using SQL.
- SQL language is standard. SQL scripts, with minor or no change, can run on any relational databases such as Snowflake, Oracle, SQL Server, MySQL, Postgresql, etc.
- Most of the data analytics/data science processes can be implemented in SQL and deployed in databases.
- SQL was developed over 50 years ago. It is still widely used and will continue to be so for many years to come. Not many programming language survived such a long period of time. It is a good investment to learn SQL.
Wednesday, June 15, 2022
Convincing an Intern to Perform Data Science Tasks Using SQL
An intern has joined my client's company to work on a data science task. I will be helping her along the way. She is familiar with Python and R programming languages and has accomplished a number of projects with these tools. However, I have successfully convinced her that it is a good idea to learn database query language SQL and use it to perform most data work. The following are the four reasons that I mentioned:
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