Is SQL Needed to be a Data Scientist?

How SQL can help you me get started with Data Science? Why is it needed?

To be a good Data Scientist, you should have some knowledge about SQL. Many beginners who are trying to get into Data Science but, worried about coding, they start with SQL queries. After that, you have to learn either **Python or R ** to learn and apply Data Science. In this blog post, firstly I am going to describe what is SQL and then, how SQL can help you to get started with Data Science.

What is SQL?

SQL (pronounced as Sequel) is a Structured Query Language . That is to say; it is a programming language, designed to manipulate data that is stored in a Relational Database Management Systems or RDBMS . It is used to insert, delete, update, modify data, etc. Remember, SQL can not write full applications. Data Scientists are using SQL to fetch the data from databases. After that, they apply some magical kinds of stuff on the data. SQL is very simple to learn, but, it is a very powerful language.

What is DBMS?

A database is an organized collection of structured data. Database Management Systems or DBMS is software for storing and retrieving data in a simple organized way. There are many SQL servers available, so, as a data scientist, you have to familiar with one of them at least. The server depends on the company you are working for, in addition, the syntax may change a little bit based on the DBMS you are using.

How do Data Scientists use SQL?

We know that the most important thing to a data scientist is data. Data may come from many sources. Data scientists may need to create their own database and then, they might store information or delete information from that. We need SQL to retrieve data from databases. After that, some data cleaning process takes place. And then subsequently, applying Machine Learning Models, training, testing, predicting, visualizing all the steps take place.

Add more points if you have. Would be great to know.

SQL is one of the four most important skills I personally test a candidate while interviewing. Yes you no need to be stored procedure or cursor expert but you should neither have a confusion between WHERE clause and HAVING clause.

There are few reasons why at least above average SQL knowledge is important. Few of them being.

  1. For an overall first cut view of the raw data, you will mostly interact with a database. If you lag in SQL skills, viewing raw data as it is stored in tables at that level becomes difficult.
  2. Never ever, you will have a master data set ready on which you run a machine learning algorithm. This master data set need to be prepared by data scientist and to do this you will have to join multiple data sources(tables mostly). Here you need a good grasp on SQL.
  3. There are lot of packages, interfaces in analytics tools like R and Python which facilitate creation of a bridge between databases(may be oracle, mssql, hive etc) and analytics tool/platform. All of this will run on SQL queries for data pull and push both ways. This entire thing demand a decent SQL skill.