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Everything you need to know about the ONLINE MSDA INFO SESSION and Q&A

When and where is the event?

The session will take place online on Wednesday, June 9 from 12:00 - 12:30 p.m. EST. If you can't make the live event, don't worry! RSVP and we'll send you the recording after. 

What will be discussed in the session?

During the session, program director, Dr. Katie P. Desiderio, and your Student Experience Mentor, Angelo Fattore, will cover:

  • Career growth and opportunity in the Data Analytics field
  • Why an MSDA is worth it
  • What the difference is between an MSDA and other master’s degrees
  • The program’s leadership and communication focus, actionable learning, and 360-degree approach 
  • How to take advantage of GMAT waivers, prior course credits, and tuition assistance 
  • What to do if you are missing prerequisites
  • The program overview, plan of study/format, and faculty
  • What the student experience is like
  • How to apply and prepare for the program

We’re also happy to answer any questions you may have in our Q&A.

How can I join?

All you need to do is RSVP and we'll send you the join link. We'll follow up with a reminder email the day of the event.

Meet the speakers

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Angelo Fattore, Student Experience Mentor (SEM)

Angelo Fattore is the Student Experience Mentor (SEM) for all graduate business programs at Moravian. He is a Moravian Alum who spent several of the past few years working internationally before landing back in his college home to work and pursue his MBA.
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Dr. Katie P. Desiderio, Program Director

Dr. Desiderio earned an MBA from Wilkes University and a Doctorate in leadership with a specialization in HR development from Barry University. Her research interests are in the area of employee engagement and human connection associated with happiness and performance at work.
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Professor Joseph Szmania, PhD, Adjunct Faculty

Professor Szmania earned his MA and PhD degrees in Economics from New York University.  With business experience spanning 35 years, his analytic work has included developing and programming algorithms used for predictive modeling, market research and in regulatory matters.