The role of the data scientist is key among companies analyzing big data and looking to make sense of it for decision-making.
The Makings of a Strong Data Scientist
Predictive analysis requires a strong mind, an understanding of big data sets and structured and unstructured data, and the ability to use this information in an unbiased way to help a company make important decisions. The ideal data scientist must be knowledgeable in IT, with analytical skills and statistical insight.
“Degrees in mathematics, statistics, and science, as well as database skills in software such as SQL, are desirable qualifications,” according to FedTechMagazine. “Data science is emerging as a discrete specialty within computer science.”
There are various data scientist degrees and curriculums offered by a number of universities. However, the ideal person really has to have a lot of experience with different technologies or sciences and preferably be a PhD. They will also command a hefty salary – $150K to $250K – because they are in such high demand.
Charles Roe writes an interesting piece for people looking to make a career of data science. He emphasizes knowledge in a number of areas including mathematics, statistical analysis, data mining, data modeling, visualization, and even creativity and innovation.
How Do You Know if Your Company Needs a Data Scientist?
So the question remains, does your company need this professional in today’s world, or are there tools that can do the same job as a data scientist?
The answer really depends on the type and size of your company. Data scientists play major roles and are great assets within larger enterprises and companies, tackling big data on a massive scale. However, for smaller companies with tighter budgets and smaller IT teams, there may be alternatives that make more sense than having full-time data scientists on staff.
This is because, as Forbes notes, there are companies offering tools or services with automation that are starting to take over some of the key tasks of the data scientist.
The Forbes’ article concludes that there will always be the need for a data scientist to some degree. The need will always be there for larger enterprises and companies looking into big data for business intelligence on a massive scale.
This is what separates big companies that need at least one, or possibly a team of data scientists, from budget-conscious businesses and smaller firms that need to look at other means of analytics.
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