What is Data Science?

Hello Friends,

There is a lot of buzz in the industry around Data science these days. You may come across many people talking about better job opportunities as a Data Scientist.
But, the question that arises here is what exactly is Data Science?

Today a lot of raw data is being generated via social media sites etc. This data can be anything from images, videos, text, etc. which is either structured or unstructured. This Data is coined as Big Data. This Data needs processing to generate some meaningful output which can be beneficial for the business industry. This is where Data Science comes in to picture.

In layman’s terms, Data science is nothing but an analysis of the data to output some valuable information to solve business problems.

Consider e-Commerce platforms like Flipkart, Amazon, etc. which almost everyone is aware of. Whenever we search for any product on these platforms, we also get a few recommendations about related products that we can buy along with the product we searched for. Also, we get suggestions on what other people bought along with the product that we searched for.
Now, how do the recommendations flash on our screens? This is the work of Data Science.

Consider another example wherein we searched for a particular video on Youtube. We start getting suggestions for recommended videos in the ‘UpNext’ section for the next video to be played. This particular video in the ‘UpNext’ section is determined by how many people watched the similar video we searched for currently and what video many users played next after the current video which is being played.
Also, some other day when we re-visit Youtube, we get a plethora of video suggestions similar to the video we last searched for or watched.

So, this analysis of Data and determining a particular pattern from the data and providing a predictive analysis is Data Science.

In technical terms, data science is a field that works with and analyzes large amounts of data to provide meaningful information that can be used to make decisions and solve problems. Data science includes work in computation, statistics, analytics, data mining, and programming.


Data Science is a blend of machine learning algorithms, statistics, business intelligence or domain knowledge, and programming.
This helps us reveal hidden patterns from the raw data which in turn provides insights into business and manufacturing processes.

Data Science can be used for – Better Decision making, Predictive analysis, Pattern Discovery.

Data Science has experimented with online businesses first. This is because with the online platforms it becomes easy to track users every single click or movement which can then be used to analyse the pattern and generate a meaningful insight from the data.
Apart from the online businesses, few other fields where Data Science started to gain a foothold is:
– Agriculture
– Logistics
– Manufacturing/Production
– Automotive

To dive into the field of Data Science, from the aspects of the skills, you need know :
– Coding
– Statistics
– Business Knowledge or Domain Knowledge

Coding :
Coding is the main aspect of Data Science which cannot be avoided. One must have a basic knowledge of coding. The most popular data science languages are SQL, Python, and R.

Statistics :
To work with Data Science, one must be aware of the Mathematical concepts of Statistics as data is nothing but playing around with numbers.
The statistical concepts one must be aware of are:  statistical averages, statistical biases, correlation analysis, probability theory functions — machine learning algorithms.

Business Knowledge or Domain Knowledge :
In this aspect, you need to have a fair knowledge of the domain you are working with. For e.g: If you are working with the Insurance industry, you should know the basics of insurance, the business strategies of the insurance industry, etc. Without this knowledge, you won’t be able to provide meaningful output for meaningful analysis.

So data science is a blend of Coding, Statistics, and Business.


  1. Very informative blog. Looking for more such blogs Shraddha.

    1. Thank you very much.

  2. This is very informative and interesting!!

    1. Thank you very much

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