Data Science: The Most Popular Course of the 21st Century


The world is being flooded with a huge amount of data that is being distributed daily in companies. The rise of the internet and the introduction of social media platforms have led to an extra peak in the amount of data generated. It is necessary to extract useful insights from the data to add business value, but these data sets alone can not generate a value. It requires professionals who have the expertise to process these enormous datasets and to extract insights from the data. The skilled professionals are data scientists, who are considered a combination of scientific method, technology and mathematical skills and tactics.


Data science has spread its influence in almost every sector, whether it is healthcare, education or entertainment. The widespread development and advancement in data science has proven how crucial it has become for an organization's success to outperform its competitors in a cut-throat business contest.

For example, Netflix is ​​the most popular entertainment fad and is emerging as a fad under the current generation. But how, you might wonder, does this relate to data science?

Well, the type of movies and TV shows you watch affects your collection on the home page. Netflix automatically begins with presenting the movies and TV shows that you should view based on what you have already watched. This is all done by data scientists who collect and analyze the data related to your previous selections.

The same thing works with YouTube. It also recommends the videos to view based on the videos you've already watched. This task is complex because it involves the use of specific computer programs & statistical algorithms by data scientists.

The delusion of data science has forced the big Fortune 500 companies to adopt the techniques and methodologies relating to data science. This has created a need for professional data scientists.


The main responsibility of a data scientist is to collect and organize the datasets using analytical data. tools such as Hadoop, SAS, R, Python etc. All responsibilities of the data scientist are detailed below.

1) Collect, organize, analyze and interpret the datasets.

2) Understand the business problem and use both historical and current data to predict future trends.

3) Development of more innovative and advanced analytical methods.

4) Finding and exposing the hidden solutions in the mass of data for the business problems, thus adding value.

5) Presentation of the results of the data analysis in a clear and detailed way.


The buzz and craze created by data science requires that you do the job in a detailed way for pursuing a career in data science. The high salary and the prospect of a job are a big attraction. Your personal taste and your interest in numbers and patterns, however, must be the criterion that you use to determine whether this career choice suits you.

Source by Shalini Madhav

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