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Business Data Analytics

  • Bachelor of Science
Justin Petrovich stands in front of his business data analytics class

Data Analytics in a Benedictine Tradition

Modern life is increasingly built around data, necessitating a workforce and citizens equipped to understand and use it. The business data analytics major at Saint Vincent College will teach you the analytical skills and methods you need to analyze, interpret, and communicate findings from data, especially in a business setting. Following the Catholic Benedictine spirituality of the College, the curriculum also emphasizes the philosophical and ethical aspects of data analytics and helps students to integrate their analytical skillset with a broader pursuit of truth.

A student focuses on taking notes while seated at a classroom table, with classmates engaged in learning activities using laptops.

Undergraduate Programs

Program Highlights

Careers After Saint Vincent

The Bureau of Labor Statistics forecasts far above-average job growth in data-related occupations between 2021-31, coupled with high median annual salaries. As the demand for data literacy grows, the possible fields open to students studying business data analytics continue to expand. Some of the most common fields include finance and banking, healthcare, insurance, retail, public health, government, computing and technology, sports, and energy. While many companies explicitly hire data analysts or business analysts, the business analytics skillset is desirable for many other job positions as well. At SVC, we prepare students for their careers through a rigorous and enriching curriculum, internships, and a client-facing capstone project that integrates their various data analytic skills and showcases their creativity.

Alumni will go on to successful careers as

  • Advanced analytics analysts
  • Business analysts
  • Data engineers
  • Market researchers
  • Operations research analysts
  • Quantitative analysts
  • Sales and operation execution analysts

Our students have secured jobs and internships at a variety of companies in their field and enrolled in prestigious graduate schools.

  • ADUSA Procurement
  • Booz Allen Hamilton
  • Federated Hermes
  • General Dynamics
  • Kennametal
  • Lockheed Martin
  • Mid Penn Bank
  • PNC
  • Stellar One
  • Vision33
  • MS in Operational Excellence at Saint Vincent College

Student Success Stories

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    Jordan Sabol, C'23

    "I chose Saint Vincent College over many other options for its nationally recognized McKenna School of Business which includes an overly qualified faculty and extensive coursework. I also had the opportunity to earn a spot on the baseball team continuing my athletic career. I like the practicality of the coursework within the Business Data Analytics program as the classes I am taking can be easily translated into a future career and post-graduation success."

    Advanced Analytics Analyst, Federated Hermes

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    Marla Turk, C'17

    “I applied to a few schools, but after I applied to Saint Vincent College I got a call from Dr. Gary Quinlivan, Dean of the McKenna Business School. We talked about the Economics program and the possibilities of my career and graduate school. I had not seen that type of kindness and excitement for my personal career in any other college in my search. I found a real passion in analytics/statistics and I learned so much about the world through all of the trips and student experiences. The people I met shaped me.”

    Senior Analyst, Customer Behavior Analysis, MGM Resorts International

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    Jeremy DalleTezze, C'02

    "The rise of ‘smart’ and ‘connected’ products is a significant trend with no end in sight. At the core of this attached software, and its value add in this context, is data. With every product moving toward data-driven software and services, and every management decision being data-informed, companies need data savvy employees in every department.”

    VP of Analytics, Technology Services Industry Association

Curriculum Requirements

The business data analytics major is part of the  Alex G. McKenna School of Business, Economics, and Government and is supported by our core curriculum, where students delve into diverse academic subjects at both foundational and advanced levels to explore how different disciplines connect, fostering deeper self-understanding and proficiency in their chosen field of study.

  • Required Courses

    Data Analytics major requirements - 32 credits

    Required courses: (26 credits)

    CS 1xx Introduction to Python
    DS100 Intro. Data Science and Analytics
    BA 355 Advanced Business Analytics
    DS300 Methods of Data Science and Analytics
    DS350 Data Mining
    EC360+361 Econometrics with R lab
    BA 106 Data Visualization
    BA 107 Relational Databases for Business Analytics
    DS400 Data Science and Analytics Capstone

    Plus choose one from the following: (3 credits)

    BA 353 International Finance
    BA 395 Global Marketing
    BA 251 International Business
    BA 250 Global Business Management

    And choose one from the following: (3 credits)

    BA 397 Marketing Research
    BA 335 Digital Marketing Analytics
    CA 344 Sports Analytics
    BA 364 Introduction to ERP Systems
    BA 368 SAP Business One Program
    BA 420 Accounting Information Systems

  • Key Courses

    Students studying business data analytics will develop strong analytic and statistics skills built on an understanding of the core business competencies. They will learn to make data-driven decisions with an emphasis on using data to identify trends, create informative visualizations, and explain relationships.

    Econometrics with R Programming Lab: This course builds on the principles and methods learned in the business statistics sequence. It is an introduction to regression and correlation analysis, multiple regression, their uses, and related problems such as multicollinearity, serial correlation, and heteroskedasticity. The course is balanced between theoretical development and applications.

    Advanced Business Analytics: This course introduces advanced data analytic tools specific to business applications. Through case studies, topics in descriptive and predictive analytics will be covered, including supervised and unsupervised learning techniques, risk analysis, and sensitivity analysis. Coverage of these topics will emphasize conceptual understanding, interpretation, and communication through group presentations.

    Data Science and Analytics Capstone: Students will work in teams to complete a data analysis project through all the project stages, including developing appropriate questions, data mining, cleansing, transformation, and appropriate analysis using data tools, visualization of the results of the analysis, and communication to the client. Students will also explore responsible conduct of research and other ethical considerations.

Undergraduate Programs