In 2012, the Harvard Business Review called the Data Scientist “The Sexiest Job of the 21st Century.” Six years later, people are still not exactly certain what data science is, and how it differs from the statistics field.
While data science certainly uses statistics in its analyses, it also uses machine learning, and other similar scientific methods, processes, algorithms, and systems to extract information from data.
A major component of data science involves trying to find consistent patterns in data to allow scientists to make predictions. Often these patterns are very complex, involving fractal, biotic, and stochastic patterns traditional methods would typically miss. The data can be from a single source or a multitude of sources. The advent of data science has in fact resulted in a call for scientists to “free the data” and make all data available to everyone.
Businesses that use statistical analyses can likely use data science analyses as well. Data on raw materials, physical capital, sales, employment patterns, stocks, commodities trading, and almost anything else imaginable can be analyzed to try to find these complex patterns that often hide information in plain sight. A lot of data sets can look like a bunch of noise, but there are in fact patterns that can with the right analyses be quite easily discovered.
All of these are pattern predictions of course, and pattern predictions will never have the kind of precision enjoyed by physical engineers. Even data science could not give as precise a prediction as the stock market crash taking place in September of 2008, let alone it taking place on Sept. 29 specifically, but it could have predicted that the economy would be in trouble within a year or two of sometime in 2007, given the data available that year. Such information may be enough to save a business.
This is just one potential scenario for how data science can be used to help a business. Each business is different, and unique data will impact businesses in varied ways. Whether it is stock market patterns, future worker shortages in a field, investment patterns, or sales patterns, just to name a few, businesses can use data science to analyze large quantities of data that can help them survive through tough times and to succeed even more when the economy is booming.
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