Data Science is Important!

By Admin Published in Data Science 5-7 mins
Table of content
Related Posts
Win the COVID-19

April 24, 2021

Model vs Algorithm in ML

April 29, 2021

Is AI a threat to humanity?
Akash Kumar

August 18, 2019

Tuples - An Immutable Derived Datatype
Vineeth Kumar

August 18, 2022

Young Data Scientists

December 17, 2021

Random forest model(RFM)

December 20, 2020

Data Science is Important!

December, 2021

Data Science at Intern Level

January 7, 2022

Text Stemming In NLP

July 5, 2022

Clustering & Types Of Clustering

November 17, 2020

Support Vector Machine

November 25, 2020

Operators in Python - Operation using Symbol
Vineeth Kumar

September 14, 2022

Basics of Functions In Python - A Glance
Vineeth Kumar

September 9, 2022

Data Science is Important - Why We Need it?

Yes you read that right, you need Data Science and so does everyone! Irrespective of the domain you work in, your educational background or if you are a tech-head or a non-tech person, you will still be in need of Data Science. Ask me how. There is a typical notion of one will end up being only a Data Scientist by pursuing Data Science, Well, this is half the truth, while the fact is, by pursuing Data Science you could become anything. (anything is only limited to technical growth, of course)

‘Anything’ does not count superpowers of course, but it means that you could survive anytime in the technical world. If you just notice the definition of Data Science you may get my point. The definition goes by, Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Since it is a multidisciplinary field the aspirants will get to have knowledge on diverse languages and various tools, which will not only work inside the field of Data Science but also in any field of technology. Because Field of Technology is a vast land that bears all the technologies that has ever existed so far and Data Science is only one of its part.

_Lets first get what will one get to study in Data Science, that is:

Python, R programming, Java, SQL, Scala, Tensorflow, Matlab.

The above tools and languages are the essentially used tools and languages in the field of Data Science, now I will tell you the uses of each of these tools outside the field of DS.


Used in: It is generally used in developing desktop GUI applications, websites and web applications.

Reason: Python is a highly productive language with simple programming syntax’s and easy code readability, English like commands makes it easily understandable.

There are many companies and startups working especially as website developers or application developers for several different clients. Every Independent organisations like hospitals, education sectors, business industries, or even the government sectors will need a personalized stand alone application that would keep a better track of the data and a good interface to help them ease out with the typical general tasks they get to handle.


Used in: It is used in e-commerce website to android applications, is also majorly used in electronic trading system.

Reason: Java is object oriented programming language that has easy and simple methods to work with, it runs in every machine that has JVM(Java Virtual Machine), has helpful features like being platform independent, dynamic and easily portable.

Unless you weren’t under any cave, you would be aware of how much e-commerce websites like Amazon, Flipkart, banking sites, etc are growing popular everyday, which means the demand for Java will not see downfall but only get stronger.

R programming

Used in: It is generally used by Statisticians for data mining, data analysis and for major statistical approach.

Reason: It is a free software environment for statistical computing, the graphics for statistical computing are supported by R foundation.

With the knowledge of R programming one could easily merge with Statistics oriented fields.


Used in: SQL is all about working in Databases, its statements are used to perform tasks like updating data on databases, or retrieving data from various databases. Oracle, Sybase, Microsoft, SQL server, all such uses SQL.

Reason: SQL is the mainstream language that is used to access database because it can work with any database. It will help to store the data in an organised and logical manner.

Database is the main backbone for anything in the technical world, as data is the new fuel to the current generation, Database handlers are in high demand in every field that involves technology.


It is mainly used for Classification, Perception, Understanding, Discovering, Prediction and Creation of Data. It is an open source artificial intelligence library, uses data flow graphs to build models. It allows developers to create large-scale neural networks with various layers.

Artificial Intelligence is the field you will attract if you get handy with TensorFlow. As per the demand and exponential growth that AI is reaching to, we can say TensorFlow will help you out the way.

These are the tools that are essentially used in DS, there are still other concepts one will get to study in the course of Data Science which will also work in different fields of the IT field.

By studying Data Science you will not only Learn that concept but also all the important languages and tools that currently runs in the technical field. You will have wide and far better opportunities even outside the boundary of Data Science. All you need is a good place where you can learn Data Science as it will act as the foundation for your journey(know why). Data Science is so much of a diverse field that it will provide diverse opportunities even for those who are a part of it, don’t hesitate to take up Data Science, it is worth it. I hope now you know why_ Data Science is important and how much you need it.


#Data Science