Description

This course is about gaining exposure to and building capabilities towards better data-driven business decisions in the digital age. Recent MIT research shows 9% higher top line and 26% higher net margins for companies with ‘Leading Digital’ capabilities. A key aspect of the emerging digital and social media technologies is the ‘big-data analytics’ opportunities they generate. While most firm have capabilities in summarizing the data they have very few have the analytical abilities to gain true insights from such data to get business results. We will have a hands-on data-driven analytics focus through this course, and will combine techniques from statistics, machine learning, and design of experiments (aka A/B testing) to learn the state-of-the art exploratory, predictive and causal inference modeling techniques used in a variety of business contexts.

The course will use the contexts of digital and social media marketing to exemplify the role of analytics. However, the methods taught will apply to the analytics of supply chains, human resources, product design and other functional areas of business.

The course will use a mixture of lecture, online reinforcement for the hands-on component, SOBACO case studies that come with rich datasets, and will get CEMBA students comfortable with industry leading analytics tools such as Tableau, R and Rapid Miner. No prior coding or computer programming experience is necessary.

The course discussion will be complemented by cutting-edge projects and various business consulting assignments that the professor has been involved in with various companies over the last few years.

At the end of the course all students will become excellent at understanding the power of business analytics so that they can ask a richer set of questions in their organizations, and of your vendors and industry partners.

Objectives

The key goal of this course is to prepare students for the rapidly changing technological environment, as effective employees, business analysts, leaders of analytics oriented teams, and digital marketing champions. At the end of this course, students should be able to:

• Understand the state-of-the art methods of exploratory data analysis and interactive visualization
• Learn the three main methods used of predictive modeling, which serve as the foundations of big-data analytics.
• Learn the principles of A/B testing for causal inference
• Become familiar with social network analysis to leverage social media effectively
• Become experts at the fast changing world of digital marketing, learning about the interactions of display, search, mobile and social marketing.

By the end of the course students will become sophisticated users of the following techniques:

• Interactive visualization using Tableau
• Market basket analysis using association rules
• Clustering based segmentation of customer data
• Predictive classification (say to identify those most likely to respond to a marketing intervention) using Logistic Regression, k-nearest neighbors and classification trees
• Social network analysis to identify influencers and various ideas to spread social contagion
• Elasticity regressions to improve performance of digital search advertising

Important Deadlines

Please see section details for:

• Enrollment deadline
• Grading option deadline
• Cancellation and refund deadlines

Waitlist Policy

Once all alumni seats have been filled, registrants will be placed on a waitlist in case another registrant drops. It is at the discretion of the CEMBA administration and faculty to add additional seats to an elective course to accommodate wait-listed alumni.

Attendance & Grading

Courses are four 4-hour sessions held on campus at the Carlson School of Management in the Executive Center. We prefer that alumni attend all four sessions and participate fully, as they will be in class with current students.

Alumni will not receive credit for the course, but will receive a certificate of professional development upon completion, if requested. Alumni can choose to audit the course or participate fully in assignments, resulting in a letter grade. You must alert the program office of your choice by the grading option deadline in section details. This grade is not subject to the 3.67 +/- .1 median aggregate and is not reflected on or as part of your official University of Minnesota academic transcript.

Miscellaneous

• Alumni should bring a laptop with them to class.
• Alumni must activate and use their UMN internet account, as this will be used for registration, Moodle log-in, communication from professors and wireless connection. If alumni do not have an active UMN internet account, they will have to create a guest account.
• Alumni will be given nameplates to utilize during class.
• Classes will be recorded and available for review.

For more Information

If you need help or have questions about this course, please contact Tiffany Meeks at 612-626-7476 or e-mail at tnmeeks@umn.edu.