Towards Data Science

With the gradual increase in data day by day, the need for its storage also grew. This was a big challenge in front of the enterprise industries until 2010. The prime objective was to build a framework and solution to store data. This is where Data Science came to the rescue.

Today, in this article we’ll get a sneak peak into Data Science and its related infos and probably by the end of this article, you will be able to understand what Data Science is and its role in extracting meaningful insights from the complex and large sets of data. 

What is Data Science?

Data science is the field of study that integrates domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.

It can also be defined as the process of using algorithms, methods and systems to extract knowledge and insights from structured and unstructured data. It is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data.

Who is a Data Scientist?

In the most simple term, a Data Scientist is one who knows the art of Data Science. Data scientists are the ones who crack complex data problems with their strong expertise in certain scientific and mathematical disciplines. They draw a lot of information from the scientific fields and applications whether it is statistics or mathematics and apply it to the raw data to generate useful insights.

Why Data Science is Important?

Data Science is important in order to generate maximum value from a raw set of data for any business. The insights that a data scientists generates is very useful to drive business decisions and take actions intended to achieve business goals.

The Pillars of Data Science

Although there are numerous skills and expertise that are highly desirable in Data Science, but these are the four major areas in my opinion :

  • Business/Domain
  • Mathematics (Particularly Stats and Probability)
  • Computer Science
  • Communication Skills

Data Scientist vs Data Analyst vs Data Engineers

Data Analyst
Data Analyst is the one who analyzes numeric data and uses it to help companies make better decisions.

Data Engineer
The job of a Data Engineer is to prepare data.

Data Scientist
The Data Sceintist analyzes and interprets complex data.

Is it worth to go with Data Science in 2021 ?

According to the U.S. Bureau of Labor Statistics, there will be a tremendous growth in the data science field which will lead to an increase in the number of jobs by about 28% through 2026. If we convert this 28 % in numbers then it will be roughly 11.5 million new jobs in the field.

And reasons that make favour Data Science as a very good career option are the high demand for Data Scientist while the supply is still low. Also there is lack of competition for these jobs in comparison to the other trending job options. These factors combined together makes this field a very lucrative and smooth option as a career path.