There is a tremendous amount of data which is generated by every business on a daily basis. The rise of the internet and the introduction of social media platforms have led to an additional spike in the amount of data generated. It is necessary to extract useful insights from the data to add business value but these datasets alone cannot generate value. It requires professionals who have the expertise to handle these huge datasets and 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.
Applicability of Data Science:
Data science has spread its influence in almost every industry, whether healthcare, education or entertainment. The widespread development and advancement in the field of data science have proven how crucial it has become for the success of an organization in surpassing its competitors in the cut-throat business competition.
Netflix, for example, is the most popular entertainment fad and is emerging as a craze among today's generation. But how, you may wonder, does this relate to data science? Well, the type of movies and TV series you watch influences your collection on the home page. Netflix automatically starts suggesting the movies and TV shows you should watch based on what you have watched already. This is all done by data scientists collecting and analyzing the data related to your previous selections. The same thing works with YouTube. It also recommends the videos to watch based on the videos you have already viewed. This task is complex because it involves the use of specific computer programs and statistical algorithms by data scientists.
The craze of data science has forced the big Fortune 500 companies to adopt the techniques and methodologies related to data science. This has created a need for professional data scientists.
Responsibilities are associated with Data Scientists:
The prime responsibility of a data scientist is to collect the datasets and to organize it with the help of analytical tools like Hadoop, SAS, R, Python, etc. However, all of the responsibilities of the data scientist are listed below in detail.
1) Collecting, organizing, analyzing and interpreting the datasets.
2) Understanding the business problem and using both the historical and the current data to predict future trends.
3) Developing more innovative and advanced analytical methods.
4) Finding and uncovering the hidden solutions in the mass of data for the business problems, thus adding business value.
5) Presenting the results of the data analysis in a clear and detailed manner.
The buzz and the craze created by data science requires that you study the job in a detailed manner before pursuing a career in data science. The high salary and job prospects are a big draw.