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Data Science and Business Analytics
Concentration Coordinators Sanjiv Das (Finance), Xiaojing Dong (Marketing), John Heineke (Economics)
Description Many new opportunities exist for managers to apply analytical techniques to business problems. This area has experienced explosive growth due to the availability of large corporate databases, enhanced computing tools, and the analytical culture of many Silicon Valley companies. A large number of major Silicon Valley companies are managed by engineers and computer scientists, creating an expectation that managers throughout the organization are able to apply the tools of modeling and data analysis to business problems. This concentration is intended to provide students with the perspective, skills, and methods for interacting with, and being an interface between, business and data science professionals in companies in the application of data science and analytics solutions to business problems. A substantial number of our MBA students come with an interest and aptitude for analytical techniques due to their technical undergraduate degrees and related work experience.
Students in this concentration will need a strong background in probability, statistics, regression analysis, and calculus.
The motivations for this concentration are:
Courses fulfilling concentration
Select five courses from those listed below:
Job Possibilities: Data Science Concentration Graduates
Positions graduates will be ready for range from highly technical business data analysts to entry level data scientists. A person working in a data science environment today needs to know how (a) to ask relevant and sharply focused questions of business data, (b) to access data and use software languages to answer those questions, (c) to present results and visualizations, (d) to communicate effectively with non-technical management, (e) to understand business paradigms in the field, and (f) to critically evaluate the work of data scientists. Our academic advisory board for the concentration is made up of top data scientists at LinkedIn, Yahoo!, Macys, and Acxiom. They suggest that this chain of skills is critically needed. They believe that data scientists not only include computer scientists well versed in Big Data, but also those who understand markets, the tools of data science, the paradigms of business, and are able to pose fundamental business questions.
For example, it is not important to know the technical aspects of cloud computing, but one should know what it is and where it fits into the business strategies of firms. It is not important to be able to write sophisticated software or regression analysis tools, but it is necessary to know how to design and undertake regressions using the appropriate software to thoughtfully address the question at hand. Extensive knowledge of database engineering is not needed, but being able to extract data from databases to run analyses is needed. Modern day data analytics goes well beyond running Excel, so the skill set must include stronger analytic tools.
When a student is able to pose good questions, identify basic problems, and has the skills to use data well, within the appropriate economic paradigms, the student’s skill set will be applicable to a wide set of disciplines in business. The spillover benefits are wide-ranging, as students will find that courses in this concentration prepare them to be much more adept, both conceptually and technically, in other courses in the usual disciplines of marketing, finance, economics etc.
Last update July 2015