Master of Science in Data Analytics (Online/Asynchronous Program)

Study at your own pace online (asynchronously)

Program Overview: Asynchronous Master of Science in Data Analytics

• Equips students with critical skills to become Data Analysts or Data Scientists across industries.
• Focuses on the integration of Data Analytics and Informatics to drive organizational decisions.
• Prepares students to:
  • Analyze real-world situations and everyday activities.
  • Synthesize and mine big data.
  • Uncover patterns, relationships, and trends.
• Responds to the growing demand for data-driven decision-makers in business and technology.

Concentrations are available in:

1. Technology/Database
2. Business

Key Learning Areas

• Big data analytics and interpretation
• Statistical methods and quantitative analysis
• Data modeling and warehousing
• Data mining and pattern recognition
• Analytical thinking and visualization tools
• Business intelligence and predictive modeling

Online Course Experience

• Courses developed by professors and professional instructional designers.
• Designed for engaging, consistent online learning.
• Features include:
  • Clear expectations
  • Varied learning activities
  • Multiple interaction formats
• Flexibility to study anytime, anywhere, with structured deadlines.
• Courses match the academic rigor and standards of on-campus offerings.
• Supported by expert instructors and a dedicated online learning team.
• Faculty monitor each student's progress throughout the semester and are available to support students with any questions, issues, or concerns.
• Internships allow students to apply knowledge in real-world settings.

Mode of Delivery for Courses

• Delivered via Canvas Learning Management System (LMS).
• Structured into learning modules:
  • Assigned readings
  • Recorded video lectures or narrated slides
  • Discussion boards and peer interaction
  • Assignments, quizzes, or projects
• Flexible log-in schedule to accommodate work and life balance.
• Expectations and due dates clearly outlined in both the syllabus and module.

Career Opportunities

Data Analytics Program Requirements

MDAN 623

Statistics for Data Analytics

This course introduces univariate data analysis methods using statistics. Data visualization methods and practices, and an overview of sampling techniques for data collection. Specifically, this course teaches introductory statistical methods for the analysis and visualization of data and basic concepts of probability theory. Course topics include descriptive statistics, data visualization techniques, an introduction to statistical inference (confidence intervals and hypothesis testing) for decision making, linear regression models, data sampling techniques. The students will learn the statistical package SPSS to analyze data sets from real-world applications which will be discussed in class.
3 Credits

MSIN 627

Multi-Dimensional Analytics and Visualization

The course introduces the practice of managing data as corporate assets by organizations to gain competitive advantage and meet regulatory demand. The course will also describe the data management emerging profession, and skills required to perform the various data management functions for each role.
Prerequisite: MSIN 615
3 Credits

MSIN 637

Principles of Data Analytics

This course is a hands-on introduction to the field of Data Analytics where students will learn the concepts and tools needed throughout the analysis process from formulating the research question to obtaining, cleaning, and collating data to making inferences and publishing results. Students will also learn how to formulate research questions in “data terms” so that it can be analyzed and identify the limitations imposed by the available data. Students will become versed in sorting data, filtering data and creating data totals. They will learn how to use Pivot Tables. They will also master Statistical Functions, Text Functions, Database Functions, Lookup Functions, and Date and Time Functions among others. Students will be introduced to data types, control structures, functions, and debugging tools. They will learn how to acquire data, what it means to clean data by removing inconsistencies and reformat data so that it can be analyzed by statistical tools.
Corerequisite: MSIN 616
3 Credits

MDAN 615

Internship

This internship course provides candidates with an opportunity to gain both theoretical and practical knowledge in the field. Candidates will work in a professional environment for a minimum of 280 hours. This internship should draw on the skills and knowledge gained throughout the program. Regular progress reporting is expected throughout the internship. International students are required to apply for CPT for eligibility to work during their internship. The Internship MUST be approved in advance by the Program Chair.
3 Credits

MDAN 617

Advanced Research in Data Analytics

The Advanced Research course is designed to give students an individualized research, project including reading and reporting on a specific topic approved by an instructor. The subject, topics and related material must be relevant and advanced regarding data analytics either from a technology perspective or from a business perspective depending on the student's area of concentration.
3 Credits

MSIN 681, 682, 683

Professional Internship Experience 1, 2, 3

These courses provide students with the opportunity to integrate skills presented during course work into real world practice, as well as enhance their awareness of technology in their respective profession. The students will utilize their work as a means of enhancing the educational experience, making on-going strides academically with their professional work. The students will work in a professional environment for a minimum of 240 hours. Students are expected to secure an internship independently. International students are required to apply for CPT for eligibility to work during their internship. Weekly logs and examples of work are required for the successful completion of the internship, and are reviewed by the Faculty Internship Coordinator, upon completion of the internship. The purpose of the internship is to provide students with practical, hands-on experience in their chosen field of expertise to complement their coursework. The Internship MUST be approved in advance by the Program Chair. Students may enroll in MSIN 681 only during the fall or spring semester. MSIN 683 will require students to complete one professional certification at the end of the course to demonstrate their proficiency in their field from the experience acquired throughout the internship and their classes.
1 Credit each

Select One Concentration in M.S. in Data Analytics

• Technology/Database Concentration
• Data analytics concentration in Business

See your selected concentration section to determine which required and elective courses you will need to take in your chosen area of study.