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Certificate in Business Analytics

The 21st century belongs to those who can think and act analytically. No longer is it good enough to make business decisions, no matter what the field, based on little more than feelings or gut reactions to events. Consumer products companies, insurance companies, banks, governments, and even sports teams are turning to Analytics to improve their bottom line and assure their survivability in this age of hyper-competition and increasingly severe externalities.

This track, designed expressly for Business Students, provide excellent training on Analytics, a critical component of 21st Business careers, whether the practitioner's primary responsibility is in a functional area (Marketing, Operations, Finance, Strategy, International Business, HR) or a vertical such as Health Care or Tourism.

The need for graduates with a strong analytical background has never been higher. Companies such as IBM, the U.S. Government, and many of the Washington area's top employers have a high demand for personnel with expertise in the traditional MBA domains but with knowledge of Analytical methods. Even in these challenging times, employment rates for those with these skills remain high.

If your passion is to succeed in the 21st century in business or government, you can find more information about the Business Analytics track in this presentation (PDF) or contact us with any questions.

For more information and to view the requirements for the certificate, please click (here).

Download the Application Form for the Certificate in Business Analytics from (here).


Course Descriptions

Descriptive Analytics

Introduction to Business Analytics (1.5 Credits)

The advancement in computing and information management technology created the opportunity for businesses to store, organize and analyze the vast amounts of their customer data. This course provides an introduction to database analytics concepts, methods and tools with concrete examples from industry applications. Students will learn the fundamentals of data analytics driven strategies in creating the leading edge Analytical Competitors in today's business environment. At the same time the course provides an introduction to the relatively more recent advancements in analytical methods on business data acquired through online channels, the new practice of Web analytics.

Predictive Analytics

Data Mining Models (3 Credits)

This course provides an introduction to data mining concepts, methods and tools with concrete examples from industry applications in marketing, finance and retail. The focus will be on some of the most popular methods for descriptive segmentation (i.e. Cluster Analysis, Association Analysis) as well as predictive segmentation (i.e. Multiple Regression, Logistic Regression, Decision Tree Methods and Neural Networks. Students will be able to apply these methods on real world data using advanced statistical analysis software such as SPSS.

Forecasting Models (1.5 Credits)

The focus of the course is on predictive analysis and use of black-box models. Emphasis will be given to identifying hidden patterns and structures in the data and exploiting these for predictions. Topics include identification of periodicities, analysis of autocorrelation and partial autocorrelations, crosscorrelation analysis and their use in model identification. Applications in finance, marketing and operations such as forecasting default rates, market share prediction, call center arrival forecasting, etc. will be presented.

Prescriptive Analytics

Optimization Models for Decision Making (1.5 Credits)

The course provides an introduction to optimization techniques for decision making with spreadsheet implementation. Topics covered include: linear programming, sensitivity analysis, networks, integer programming, goal programming, and multiple objective optimization, and nonlinear and evolutionary programming. Models discussed span all business disciplines including finance, marketing, operations, and project management. Throughout the course, learning is reinforced via hands-on computer experience using problems and cases.

Analytics Electives

Students will choose 1.5 credits from elective offerings that may include:

  • Pricing & Revenue Management (1.5 credits)
  • Supply Chain Risk Analytics (1.5 credits)
  • Marketing Analytics (3.0 credits)
  • Data Warehousing/OLAP (1.5 credits)
  • Other electives as available and approved



Quick Links

Department of Decision Sciences

The Institute for Integrating Statistics in Decision Sciences

Contact Information


The Institute for Integrating Statistics in Decision Sciences
School of Business
Funger Hall, Suite 415
2201 G Street, NW
Washington, DC 20052

Phone: 202-994-6445
Fax: 202-994-2736