Python datascience library vs SQL [closed]

Question

I am a college student and in my project, I need to store a huge amount of data so I am trying to use SQL but my project partner wants to use data science because it's in trend and also can handle a huge amount of data. So I am puzzled. Finally, we decide to use python since it has inbuilt libraries which us to use the SQL statements to handle the data. Before giving our project detail to my lecturer we first jotted down the advantage of data science using python.

Easy to use

Since I have less knowledge of runtime, python libraries will help me efficiently

The best part is it has many collections of inbuilt libraries, which will help me in my coding.

But I remain with one question, even when data science is popular so many are using SQL. So I wonder did I leave any important point.

Can anyone help me solve this?

Answer 1

I am giving you an overview of how to start with the data science in python when you want to do the project with minimum knowledge.

1. Using "data science libraries" you will learn only the basis for entry-level, which will not help you completely. So you need to ignore it and start learning it from standard tools.

2. Since you wanted to use SQL queries for your project in python, You need to learn how to have an interface with SQL and JSON server eventually. Using flat files is more advantageous than the database.

3. Now you have to decide which you want to learn first SQL or data science, most of them learn SQL then data science. But its completely your choice to learn.

If you want to know more about the Data Science then do check out the following Data Science link which will help you in understanding Data Science from scratch