How Crucial is SQL for Data Science?

How Crucial is SQL for Data Science?

SQL is a programming language that aids in managing data held in relational database management systems. Nearly 90% of structured data is stored in such databases, and should you wish to work with such data, mastering SQL is absolutely essential. SQL allows you to insert, update, delete, modify, and retrieve data with the use of simple commands. This article takes a look into the various features of this programming language that helps show the importance of SQL for data science.

Importance of SQL for Data Science

Below are some points that help highlight the importance of SQL for data science.

SQL is Easy to Learn

SQL started grabbing headlines thanks to the simplicity in its syntax and use of the English language in its coding. This makes it easier for beginners to get used to the language and to understand complex concepts that otherwise would have taken a long time to properly take grasp. SQL easily lets you query and manipulate your data for extracting insights from it with just a few lines of code, which goes a long way in helping data scientists.

A Declarative Language

SQL is a declarative language, which is a major reason why professionals opt for SQL for data science. SQL has an added advantage over conventional programming languages such as R and Python in the sense that in SQL you only need to specify what you want to do and that there is no need to specify the necessary steps for doing it. This makes undertaking complex tasks easier and less time-consuming.

Helps in Understanding Data

Data helps run the study of data science, and understanding your data forms the core of the entire art. SQL for data science provides you with the ability to explore and visualize your data for producing accurate and precise results. SQL also helps you manage all the missing and null values, outliers and other anomalies that you might encounter in your data. 

Ease of Integration

SQL, along with querying and manipulation, also aids in data visualization to a certain extent. SQL can be easily integrated with other scripting languages such as Python and R, and this helps in explaining your findings in SQL to other members of your team and organization. Some SQL libraries like SQLite, MySQLdb, etc. also allow you to connect the client application with your database. This helps make the development process easier and faster.

The importance and cruciality of SQL for data science cannot be understated. It is an amazing special-purpose programming language with a lot of functionalities that help data scientists around the world. Thus it should come as no surprise that mastering SQL for data science is a basic requisite demanded of any aspiring data scientist. We at Praxis also understand the various other tools and skills that are needed for any young aspirant to become a remarkable data scientist. And to aid you in your journey, we have managed to develop a carefully curated state of the art PGP in Data Science. This course, along with our astounding placement programs and tie-ups will give you the necessary exposure and experience needed to go out and make your mark in the world of data science. 

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