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An executive from IBM recently highlighted the need for more rigorous preparation for Big Data analytics within and beyond the financial industry inan article in the Wall Street Journal. The article outlined the dire need for qualified data scientists, how qualified business and finance students are, and how even liberal arts majors can and should be trained to employ their interdisciplinary insight and critical thinking skills.
These workers must of course be trained to understand the multitude of data types and how they are analyzed. However, what if automated analysis was a tool that all budding data scientists had at their disposal? When hoards of information can be analyzed for patterns automatically, data scientists can quickly and conveniently bypass a stage in analysis that is more manual and begs for lots of time and energy.