Data Analysis for Decision Making

Course 5 of 7: MBA Core Curriculum MicroMaster Program 7 Weeks 8 - 10 hours each week
735

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About this course

In our information age, companies have access to unprecedented amounts information on customers–their behaviors, interests, and buying habits–and the markets in which they operate. Being able to analyze that data has become a critical skill for decision makers at every level of an organization. Today’s firms use data to detect market movement before it becomes a fully-fledged trend, helping them to stay ahead of the curve, tailor products and services to specific customer segments, determine when and when to enter markets, and differentiate themselves from competitors.

In this course, you will learn how to unlock the value of data to create and grow an organization. You will gain the analytical tools necessary to confidently describe the current state of areas critical to your business, predict the likelihood of an event occurring, compare two or more approaches to a business challenge, and determine if a phenomenon you are seeing is coincidence or a genuine insight. By the end of this course, you know how to make data-driven decisions to find advantages and stay competitive.

 

What you’ll learn

  • How to separate randomness from truly correlated and potentially causative variables.
  • How to determine if certain variables (e.g., your firm’s spending on advertising or sales personnel) are related to or are driving other variables (e.g., your sales)
  • How to generate forecasts of future demand, and how trends, seasonality, and extreme events, along with random noise impact our ability to predict the future
  • How to effectively visualize these relationships using the latest in data visualization tools

Meet Your Instructors

P.K. Kannan

Professor of Marketing, Dean’s Chair in Marketing Science at University of Maryland P. K. Kannan is the Dean’s Chair in Marketing Science at the Robert H. Smith School of Business at the University of Maryland. His main research focus is on marketing modeling, applying statistical and econometric methods to marketing data. His current research stream focuses on attribution modeling, media mix modeling, new product/service development and customer relationship management (CRM).

Margrét Bjarnadóttir

Professor of Decision, Operations & Information Technologies at University of Maryland Dr. Margrét Vilborg Bjarnadóttir is an Assistant Professor of Management Science and Statistics in the DO&IT group. Dr. Margrét Bjarnadóttir graduated from MIT's Operations Research Center in 2008, defending her thesis titled “Data Driven Approach to Health Care, Application Using Claims Data”. Dr. Bjarnadóttir specializes in operations research methods using large scale data; her research centers around data driven decision making, combining optimization modeling with data analytics.

Lingling Zhang

Assistant Professor of Marketing at University of Maryland Professor Zhang received her doctorate in Marketing from Harvard Business School in 2016. She is interested in studying marketing strategies using empirical methods including industrial organization and machine learning. Her research focuses on business-to-business marketing, multi-channel marketing, and digital marketing. She has presented research at the INFORMS Marketing Science Conference and the Marketing Dynamics Conference. She teaches Statistical Programming for Customer Analytics in the MS Marketing Analytics program and Marketing Research Method in the undergraduate program.

Kislaya Prasad

Kislaya Prasad is a Research Professor in the Decision, Operations & Information Technology department, and the Academic Director of the Smith School’s Center for Global Business. Prasad received his Ph.D. in Economics and M.S. in Computer Science from Syracuse University. His previous positions include Professor of Economics at Florida State University, and Research Officer at the University of Cambridge, U.K. He has also been a Visiting Professor in the Kellogg Graduate School of Management at Northwestern University and in the Economics Department at New York University, and has served as a Non-resident Senior Fellow at the Brookings Institution in Washington, D.C. His research has been published in leading economic journals and been funded by grants from the National Science Foundation. He has been the PI of four CIBE grants from the U.S. Department of Education. **** Prasad has worked on several consulting engagements with industry and with international development agencies. He teaches Economics in the PhD program, and data analytics in the EMBA, MBA, and MS programs at the Smith School. He has won numerous teaching awards, including the University Teaching Award at Florida State University in 2001-2002 and the Smith School’s Krowe Award for Teaching Excellence in 2010.
735

Duration

7 Weeks

Experience Level

Advanced

Learning Partner

University of Maryland System

Program Type

MicroMasters®

Subject

Business & Management Data Analysis & Statistics
Advanced Business Harvard X-Series