Data scientists and database scientist
The world is flooded with a huge amount of data that is produced daily in companies. The advent of the internet and the introduction of social media platforms has further increased the amount of data created. It is necessary to extract useful insights from the data to add business value, but only data sets can generate value. This requires professionals with experience to handle large data sets and extract insights from the data. Skilled professionals are data scientists, who are considered a mixture of the scientific method, technology, mathematical skills and tactics.
Data science application
Data science has spread its impact on almost every industry, be it healthcare, education or entertainment. The development and progress on a large scale in the field of data science has demonstrated how important it is for the success of any organization in overcoming its competitors in the ring business competition.
For example, Netflix is the most popular fad in entertainment and appears as a craze among today's generation. But how, you might ask, is this related to data science?
Well, the type of movies and TV series you're watching affects your group on the home page. Netflix automatically starts recommending movies and TV shows that you should watch based on what you've already watched. All of this is done by data scientists who collect and analyze data related to your previous choices.
The same thing works with YouTube. It also recommends watching videos based on videos you have already watched. This task is complex because it involves the use of specific computer programs and statistical algorithms by data scientists.
Data science madness has forced the major Fortune 500 companies to adopt technologies and methodologies related to data science. This has created a need for professional data scientists.
What are all the responsibilities associated with the life of the data scientist?
The primary responsibility of the data scientist is to collect and organize data sets with the help of analytical tools like Hadoop, SAS, R, Python, etc. However, all responsibilities of the data scientist are detailed below.
1] Collection, organization, analysis and interpretation of data sets.
2] Understand the business problem and use both historical and current data to predict future trends.
3] Develop more innovative and advanced analytical methods.
4] Finding and revealing hidden solutions in the data block of work problems, and thus adding business value.
5] Presenting the results of data analysis in a clear and detailed way.
The participation and madness created by data science requires that you study the job in a detailed manner before pursuing a career in data science. High salaries and jobs are a big draw. However, your personal tastes and interest in numbers and patterns should be the standard you use to determine whether or not this career choice suits you.