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Students majoring in Finance at Mercy College.

Business Analytics Overview

The Master of Science in Business Analytics prepares its graduates for employment in a high growth area of the economy. The program is offered to candidates who wish to enter or advance their careers in that field. 

Business Analytics graduates are in high demand, at the business world is undergoing a data revolution. Most companies are now gathering data with the objective of driving business decisions, and there is an identified and pressing lack of skilled graduates at the intersection of business and data science. 

Financial Analyst reviewing numbers for the quarter.

Career Opportunities

  • Financial analyst
  • Management analyst
  • Marketing analyst
  • Operations Research analyst
  • Operations manager
  • Analytics consultant

4 Core Competencies

  • Business acumen
  • Applied mathematical modeling
  • Computer programming skills (for business)
  • Impactful communication of analyses and results

Frequently Asked Questions

How long does it take to complete the Business Analytics Degree

The degree can be completed in one year.

Where are classes offered?

Classes are offered in Manhattan. Some courses are also offered online.

Do most students work while enrolled?

Yes. Many find the workload challenging but manageable.

Are GMATs required?

No, GMATs are not required for admittance to Mercy’s Business Analytics Program. They may be used optionally.

Program Outcomes

At the end of this program, students should be able to:

  • Students will be able to give accurate descriptions and critical thoughts on how data flows within an organization and how it adds value to the organization

  • Students will be able to utilize applicable statistical methods and tools to achieve specific outcomes using data

  • Students will be able to develop data-driven stories with the intent to:  inform, educate or persuade through analysis and visual representation of data

  • Students will be able to critically think about the role of tools in analytics, current limitations and opportunities (and needs) for growth in data and analytics

  • Students will be able to identify ethical pitfalls faced in the utilization, manipulation, and management of data in an organization

  • Students will be able to form thoughtful arguments on the role of data, automation, technology and the human processes that achieve optimal balance in decision-making in business

Program Details & Curriculum

Business Analytics M.S. Curriculum

Business Analytics Courses: 30 Credits
Total: 30 Credits

For a full curriculum listing visit our catalog.

 

Quarter 1

  • MBAA 601 Quantitative Meth Bus Research
  • ANLC 751 Introduction to Managerial Analytics
  • ANLC 753 Data Visualization

Quarter 2

  • ANLC 752 Data Management
  • ANLC 754 Fundamental Modeling Methods for Business

Quarter 3

  • ANLC 761 Risk and Uncertainty Modeling
  • ANLC 762 Advanced Modeling Methods for Business
  • ANLC 763 Analytical Tools and Applications

Quarter 4 - Elective (Choose 1)

  • ANLC 771 Customer Analytics
  • ANLC 772 Predictive Analytics for Finance
  • ANLC 773 Operations Research
  • ANLC 774 Project Management
  • ANLC 775 People Analytics

 

Capstone

 

  • ANLC 801 Capstone

Academic Program Sequence Map

Program Learning Goals

  1. Students are expected to develop a comprehensive understanding of how data flows within an organization and how data and associated tools add value to the organization
     
  2. Students are expected to demonstrate the ability to apply quantitative methods to manipulate data in order to formulate strategic insights with it
     
  3. Students are expected to demonstrate effective professional written, oral, and presentation skills of complex quantitative data
     
  4. Student are expected develop a broader perspective of the future of analytics and emerging tools and methodologies
     
  5. Students are expected to evaluate ethical issues in analyzing, utilizing, and managing data
     
  6. Students are expected to develop awareness of the benefits and limitations of data and technology in order to most effectively utilize it in decision-making