The entire process of working is going through fast changes with every advance in technology. Top financial advisors and leaders now see the future completely reliant on data science.
Automation is occurring in all industries, and while some jobs will become streamlined, that does not necessarily mean lowering the number of employees. With new technology, people need to reexamine software, information storage and even give up some responsibilities to Artificial Intelligence.
Statistics vs. Data Analytics
Statistics are a vital part of learning customer basis and seeing exactly what is occurring within the finance company and how it can be improved. There is a difference between analytics and statistics.
Vincent Granville, data scientist and data software pioneer explains this in the simplest forms, “An estimate that is slightly biased but robust, easy to compute, and easy to interpret, is better than one that is unbiased, difficult to compute, or not robust. That's one of the differences between data science and statistics.”
Data science did evolve from a need for better statistics, and once big data arrived, the standard statistical models could not handle it. “Statisticians claim that their methods apply to big data. Data scientists claim that their methods do not apply to small data,” Vincent ...
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