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PREPARING ANALYTICAL BUSINESS LEADERS
MS Business Analytics and Information Management (MS BAIM)

Master of Science in Business Analytics and Information Management

#6

MASTERS IN BUSINESS ANALYTICS

United States

QS, 2021

There is a constantly growing demand for technical and analytical expertise in the business world. Businesses are collecting more data than ever before, and using that data to make better-informed decisions is becoming a requirement.

Are you hungry to meet that demand?

Our Master of Science in Business Analytics and Information Management (MSBAIM) program will acquaint you with state-of-the-art information technologies and analytical techniques that will benefit all levels of an organization. You'll develop proficiencies in the use of Python, Rstudio, Excel, SQL, SAS, Minitab, Gurobi, and various other big data technologies.

For decades, the Krannert School of Management has used an analytical business approach to develop industry leaders. Our rigorous curriculum and experiential learning help develop students who aim to build upon their science, technology, engineering, and math (STEM) backgrounds to establish, lead, and grow prominent organizations.

Krannert is also home to Krenicki Center for Business Analytics & Machine Learning, a hub for businesses to connect with Purdue researchers to find answers to data-driven business challenges. The center also hosts multiple student-led consulting projects, conferences, and competitions.

Take the Next Giant Leap

Learn more about our MSBAIM program using the menu options. When you’re ready to move forward, we’re here to answer your questions, meet with you, and help jumpstart your application.

97 percent placement for the 2020 class, stem designated

 

  



A Conversation about the MSBAIM Program

We sat down with Krannert's Assistant Academic Director for the MS Business Analytics and Information Management (MSBAIM) program, Yang Wang, as well as program manager Mary Mitchell to discuss what you can do with a MSBAIM degree and why it matters in today’s data-driven world. Transcript