Different data science roles and why they are important in business

Data science is flourishing and there is no doubt regarding that, but there is a problem regarding different roles and jobs that are played in this industry. 84% of companies and enterprises have incorporated big data techniques in their business fold, giving rise to a variety of jobs in this sector.

However, a data science aspirant remains pretty clueless till the very end of their training about different roles in this industry and what their respective tasks are.

One can choose different roles depending on their talents and skills, but before selecting, one should be very clear about the tasks each job holder needs to perform and how they complete the entire big data cycle. Some of the very important roles which should not be confused with others are mentioned below.

Data scientists

This is the role that is most heard about and also most sought after by freshers and aspirants. This is one of the most highly paid data science jobs and is usually demanded in big companies and enterprises.

They collect and use techniques on data to give insights to the management regarding different problems. They are adept in handling and finding meaning from the crude data.

Data Architect

Data scientists and analysts can work only if there is an accurate and well-handled data for collecting and maintaining the data and their sources industries look for data architects. They are mostly demanded in sectors which handle a lot of data like FMCG, retail, finance, etc. They protect the data and integrate them into the data science cycle so that analysts can work on it. There are various data handling and maintaining technologies like Spark which a data architect need to be highly skilled in.

Data analysts

Data analyst jobs are just like data, scientists jobs, but with more analytical knowledge and skillset. They need to be highly trained and versed in using Python, R, SQL, etc. as they help in analyzing the data and find patterns in them which in turn will be helpful for the management to take timely decisions.

Statistician

Today, finding statisticians in a firm can be difficult, as this role is mostly merged with other data science roles. However, if found, statisticians are the ones who have created the foundation for data science. They use their statistical methods, techniques, and theories to collect the data and then find real meaning hidden in them. Today, in big industries statisticians are equipped with latest technological skills and knowledge and they know exactly how to extract patterns from the data.

Database administrator

Data, whether collected from internal sources or external, should be kept safe from any kind of malicious software or perpetrator. Also, the databases should be organized and made accessible to every data science team members and other management people without any glitch. This is taken care of by the database administrators as they use their skills in XML, SQL, Java, etc. to keep the database safe and organized.

Business analysts

This is a nontechnical profile as they do not really dwell on technical aspects using different technologies and methods of data science. Business analysts are the one who has immense knowledge about business and its different processes and how every data science end result can and should affect the business for the better.

Now, when one will think of data science roles they should be clear about the different aspects and opportunities these roles have and how a data science course can help them reach that goal.

Resource box

There are various roles, but to make oneself worthy of that role, one needs to be preparing themselves with a data science certification where one can learn the nitty-gritty of this sector. One can find the best in the market course at excelr, according to one's requirement and future goals.