Generation Data

"You have to think about the generation of data as a strategic imperative. Results will only be useful if your data collection is done with a purpose."

— Florian Zettelmeyer, Faculty Director of PDAK

The Kellogg Approach to Data Analytics

Our data analytics curriculum is built around our experience that managers may not always understand how analytics can help them solve tough business problems. Similarly, data scientists may not understand the business problem well enough to provide managers with actionable data.

Businesses need analytics-savvy MBAs who are natural problem solvers and fluent in analytics so they can manage a team of data scientists and effectively use data. As a result, our teaching philosophy is designed to be relentlessly problem-driven while taking a deep dive into methods and applications.

To determine which data analytics courses to take, students should start by determining the level of expertise they’d like to achieve.


To prepare for analytics, students should take Foundational courses, which provide the statistical and methodological foundations for data analytics. All students — regardless of their interest in data analytics — are required to take these courses.

Competitive Advantage

To obtain a working knowledge of analytics, students should also take Competitive Advantage courses. They will learn new methods to solve different business problems, and then apply these methods to large, real-world datasets.

Deep Dive

To become fluent in analytics, students should also take Deep Dive courses, which provide greater levels of methodological sophistication. Students should also consider taking an Experiential course where they can apply their analytics skills to real business problems.

The Data Analytics Pathway

Kellogg offers a distinct Data Analytics Pathway designed to give students an in-depth, cross-functional study of analytics in business. Use this guide to determine which courses are most relevant to your career path.
data analytics
1 Foundational
Business Analytics I
DECS 430-5
Business Analytics II
DECS 431
Marketing Research
MKTG 450
2 Competitive Advantage
Analytics for Strategy
STRT 469
Retail Analytics
MKTG 462
Sports and People Analytics
MORS 910-5
People Analytics and Strategy
STRT 440

Digital Marketing Analytics
MKTG 955
Customer Analytics
MKTG 482

Human and Machine Intelligence
KACI 950-5

Social Dynamics & Network Analytics
MORS 457

Health Analytics
HEMA 940-5

3 Deep Dive
Visualization for Persuasion
KACI 925-5

Data Exploration

Technology for Analytics
KMCI 930-5
Programming for Analytics
KMCI 935-0
Analytical Consulting Lab
MECN 915
Data Analytics Decisions
KMCI 940
Apply your analytics skills to live business problems.


Last edited August 10, 2017. For any questions regarding this page, please email

Watch Faculty Director Florian Zettelmeyer discuss how PDAK got started.

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