MSBA Healthcare Track Curriculum

The MS Business Analytics degree focuses on the exciting and fast-growing field of big data. Designed to teach students how to translate data into strategic business decisions, this robust technical foundation is augmented by specialized decision science courses, including linear and integer programming, optimization, and heuristic methods, preparing you for a data-driven career in strategic decision-making and operational efficiency.

Beyond technical skills, our program emphasizes the strategic aspects of decision sciences. Learn to synthesize data into actionable insights, understanding the implications for business processes, risk management, and strategic planning. You'll graduate with the acumen to guide data-driven decision-making, providing strategic and operational insights that shape business outcomes and drive success.

Gain three critical skills by graduation:

  1. How to capture and analyze complex structured and unstructured data sets
  2. How to develop your intuition about where business value can be found and articulated to leadership
  3. How to deliver quantitative analysis in a format that C-suite executives can understand and use

Curriculum Overview

Summer B Term- 6 credits
(June to July)

Designed as an introduction to Business Analytics, which considers the extensive use of data, methods and fact-based management to support and improve decision making. Business intelligence focuses on data handling, queries and reports to generate information associated with products, services and customers, business analytics uses data and models to explain business performance and how it can be improved. The class will be built on heavy hands-on coding; it will introduce and subsequently involve extensive use of Python.

Exposes the students to commonly used platforms for statistical and predictive analytics. The class will go into depth of analytics using R before demonstrating the same concepts using SPSS and SAS. Students will learn to analyze large datasets, including textual analytics such as twitter-stream analysis using R.


Fall Term - 12 credits
(August to December)

This course exposes the students to commonly used platforms for statistical and predictive analytics. The class will go into depth of analytics using Python. Students will learn to analyze large datasets, including textual analytics such as twitter-stream analysis. The class will focus on predictive analytics. 

Explores both the functional and technical environment for the creation, storage and use of the most prevalent source and type of data for business analysis, ERP and related structured data. Students will learn how to access and leverage information via SQL for analysis, aggregation to visualization, create dashboards, and be source for business intelligence.

Explores the capabilities and challenges of data-driven business decision making and prepares students to lead in analytics-driven organizations. Introduces a set of common predictive and prescriptive analytics tools. Students apply the analytics tools to important decisions based on practical data sets from various companies. Analytics software packages are used extensively in the course.

[expand title="NURS 6286 Foundation of Healthcare Informatics (Fall) - | Healthcare Analytics Track Elective" style="regular"]This introductory course focuses on core concepts, skills, tools that define the informatics field and the examination of health information technologies to promote safety, improve quality, foster consumer-centered care, and efficiency. [/expand]

Spring Term - 15 credits
(January to May)

Moves the student beyond structured data and sources into business scenarios where data is semi-structured to unstructured such as those from social and web applications. Specific topics include introduction to SQL-on-Hadoop, NoSQL and related distributed processing technologies. Students will learn practical application and mechanisms for getting this sort of data ready for analytics

Moves the student beyond structured data and sources into business scenarios where data is semi-structured to unstructured such as those from social and web applications. Specific topics include introduction to SQL-on-Hadoop, NoSQL and related distributed processing technologies. Students will learn practical application and mechanisms for getting this sort of data ready for analytics.

This course focuses on a structured approach to information system development and implementation. The course addresses the five phases of the life cycle: planning, analysis, design, implementation and evaluation.

Practitioners of natural language processing (NLP) use methods from math, science, engineering and linguistics to teach computers to understand human language. Because much biomedical information is stored as text, there are many possible applications of NLP in health sciences. This course offers an introduction to NLP for the health sciences. Students will gain a conceptual and hands-on introduction to fundamental tools, concepts and problems from NLP by exploring applications in healthcare, population health and biomedicine.

In Track-Specific Elective Courses:

NURS 6286 Foundation of Healthcare Informatics (Fall) - This introductory course focuses on core concepts, skills, tools that define the informatics field and the examination of health information technologies to promote safety, improve quality, foster consumer-centered care, and efficiency


NURS 6290 Information Systems Life Cycle (Spring) - This course focuses on a structured approach to information system, development, and implementation in healthcare settings. The course addresses the phases of the information systems life cycle.


MSBX 5425 Healthcare Analytics (Spring) - Practitioners of natural language processing (NLP) use methods from math, science, engineering and linguistics to teach computers to understand human language. Because much biomedical information is stored as text, there are many possible applications of NLP in health sciences. This course offers an introduction to NLP for the health sciences. Students will gain a conceptual and hands-on introduction to fundamental tools, concepts and problems from NLP by exploring applications in healthcare, population health and biomedicine.