A team of seven students in the MS in Business Analytics program won the 2023 Graduate Datathon, presented in collaboration with Under Armour.

LeBow graduate students delved into data analysis for a business analytics capstone course, in collaboration with national retail brand Anthropologie.

After a difficult international transition, an internship with T-Mobile turned things around for MS in Business Analytics student Harish Thalinki ’22.

Three LeBow students teamed up for a second-place finish in the University of Southern California’s first-ever Global Supply Chain Case Competition.

Five LeBow alumni and one longtime faculty member were recognized by Drexel’s Alumni Board of Governors.

A recent MBA graduate, Spurthi found a community through Drexel’s Graduate Student Association and made deep connections throughout her studies.

Undergraduate students in LeBow’s BRIDGE program combined service, networking and show-business excitement at stops in San Diego, Orange County and Los Angeles.

Through marketing know-how and entrepreneurial spirit, Porte has developed Sasas Mix, a gluten-free, vegan banana bread mix, into a growing start-up business.

Professor Matthew Schneider, PhD, and PhD student Jade Zhang are partnering with Forecasting for Social Good to improve privacy and effect positive change.

Leadership roles in student organizations and on competition-winning teams have distinguished his time as a LeBow undergraduate student.

Research from LeBow’s Center for Business Analytics, in collaboration with data integrity company Precisely, shows the impact of data governance programs.

New classes explore timely business topics, keeping you on track toward your degree while giving you the chance to branch out into new areas.

Satchel Manchester was among the first students to declare a major in esport business, combining an interest in business with professional gaming experience.

The LeBow community welcomes new faculty members in accounting, decision sciences, finance, marketing and sport business.

Matthew Schneider, PhD, and his co-author have proposed a new methodology to shuffle survey data so individuals aren’t identifiable even if datasets go public.