Sanjiv Das : Big Data’s Big Muscle : IMF
An article written by Sanjiv Das, William and Janice Terry Professor of Finance and Business Analytics, was published by the International Money Fund and appeared in their September 2016 Finance & Development volume.
An excerpt from the piece:
The world has access to more data now than was conceivable even a decade ago. Businesses are accumulating new data faster than they can organize and make sense of it. They now have to figure out how to use this massive amount of data to make better decisions and sharpen their performance.
The new field of data science seeks to extract actionable knowledge from data, especially big data—extremely large data sets that can be analyzed to reveal patterns, trends, and associations. Data science extends from data collection and organization to analysis and insight, and ultimately to the practical implementation of what was learned. This field intersects with all human activity—and economics, finance, and business are no exception.
Data science brings the tools of machine learning—a type of artificial intelligence that gives computers the ability to learn without explicit programming (Samuel, 1959). These tools, coupled with vast quantities of data, have the potential to change the entire landscape of business management and economic policy analysis.
Some of the changes offer much promise.
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