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Master of Science in Decision Sciences (MS), University of Colorado Denver Business School (CU Denver)

Business School, University of Colorado Denver
 

Big Data Specialization | Business Analytics


Data scientists trained in big data methods are in high demand by industry and government. In 2013, for example, New Vantage Partners reported that 91% of Fortune 1000 companies have big data efforts planned or in progress, while another 60% have already implemented a big data initiative. Interest in big data analytics stems from its demonstrated ability to transform massive amounts of unprocessed data into improved decision-making.

Social media posts, retail transactions, supply chain networks, electronic medical records, and other information sources provide input to big data projects. Data reduction methods then produce descriptive or predictive models of business processes. Predictive analytics, for example, might focus on micro-targeting individual customers using models that produce probabilistic statements about future consumer behavior.

The Big Data specialization seeks to familiarize students with the mathematical models needed to successfully analyze massive data sets, including statistical analysis, optimization models, forecasting methods, data mining, and predictive analytics. Those pursuing the big data specialization will become acquainted with:

  • Managing, retrieving, cleansing, and exploring large data sets
  • Building and testing mathematical models of big data
  • Effectively communicating the value of the project and results to others in the organization

Requirements

Choose three of the following four classes to satisfy the big data specialization:

  • Computing for Business Analytics (BANA 6620)
  • Predictive Modeling with Big Data (BANA 6710)
  • A “Big Data” Practicum Class
  • A “Big Data” Special Topics Class

Note that not all Practicum and Special Topics classes satisfy the Big Data Specialization. Because the “big data” special topics and practicum classes change from year to year, consult the tentative schedule of classes to design your course of study.

For more details, please schedule an appointment with an advisor.

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