Master of Science in Data Analytics

Master of Science in Data Analytics (MSDA) Degree Program Overview

Data analytics involves examining information to find resourceful facts and figures for making business decisions. Despite this simple definition, the field of study can be highly complex and features numerous steps. At Fairfax University of America, the Master of Science in Data Analytics (MSDA) program helps students of varying experiential and educational backgrounds develop essentials skills in data analysis and achieve their professional goals.

Master of Science in Data Analytics Degree Program Objectives

Our master’s in data analytics degree is ideal for undergraduate students who do not have a bachelor’s in computer science, as well as computer professionals who want to enhance their knowledge. Individuals who participate in the MSDA program will develop competency in the following areas:

  • Utilizing data analysis and modeling strategies to create software and solve real-world challenges
  • Communicating findings to individuals and teams
  • Organizing data into visuals that share the most critical information for presentations
  • Leveraging statistical algorithms for data analysis to better decision-making processes
  • Exercising the ethical, legal, and social standards surrounding technologies and their applications in this field

MSDA Degree Program Course Work

The MSDA program comprises a combination of core courses, career applications, and specializations. Students must earn 36 credits across these course categories to graduate. This coursework includes theoretical and practical instruction and goes over established and emerging concepts in the field of data analytics.

Before enrolling in this program, students need foundational skills to understand the material. The curriculum overview lists prerequisite courses students should take for the MSDA program. Students also must fulfill other criteria to apply for this degree, found on our list of graduate program admission requirements.

What Are Micro-Credentials?

Micro-credentials are quick, flexible programs that provide learners with training in specific areas. Students earn micro-credentials to meet their educational requirements and increase potential career opportunities. These credentials are available to undergraduate and graduate students at our university, but non-degree learners also can access them at an affordable cost.

Our Office of Micro-Credentials partners with the global digital badging platform, Credly, to give students a way to verify their efforts. Once they complete the required courses, they receive a digital badge stating they achieved the capability. Micro-credentials associated with the data analytics program include:

  • Data Analyst (DA)
  • Principal Data Scientist (PDS)
  • Big Data Architect (BDA)
  • Big Data Analyst (BDA)
  • Data Warehouse Engineer (DWE)
  • Business Analysis Engineer (BAE)

Career Outlook With A Data Analytics Degree

No matter the industry, every organization uses big data to inform its decisions. Numerous job opportunities exist for those who study data analytics. Earning a master’s degree can boost your chances of getting a rewarding job, as it proves you have the advanced educational experience to perform various tasks related to the field. Below is a list of possible career paths to seek after graduating from the MSDA program, along with average salaries according to the U.S. Bureau of Labor Statistics (BLS):

  • Big-data Architect ($98,860)
  • Management Analyst ($87,660)
  • Data Scientist ($126,830)
  • Research Analyst ($85,950)
  • Data Analytics Professor ($85,540)

Earn Your Master of Science in Data Analytics

At Fairfax University of America, we believe students should have access to affordable, business-centered instruction that gives them the necessary skills to be transformative leaders in a global and multi-dimensional society. Students receive exceptional flexibility with the direction of their studies and accomplish personal and professional growth while pursuing an education.

Complete an application to enroll in classes. If you have questions about our MSDA program, you can also request information online.


Master’s in Data Analytics degree requires completion of 36 credits. Students will take 12 credits of core courses which is common with all the programs, 6 credits of career applications, and 18 credits in Data Analytics content area.

Area Number of Courses Credits
Core Courses 4 12
Career Application Courses 2 6
Specialization Courses 6 18
Total 12 36
Program Prerequisites

All new Data Analytics program students need certain basic skills to prepare them for success in the Data Analytics Program. Data Analytics degree provides a broad understanding of computer science theory and technology. Students who do not have the required background need to take some or all of the prerequisites before taking the core Courses. Thus, to be successful, students must have a background in the following courses.

Code Course Title Prerequisite Microcredentials Credits
COMP 109 Computer Algorithm and Programming Logic Using Python None 3
COMP 260 Introduction to Operating Systems COMP 109 3
COMP 270 Essentials of Networking COMP 109 3
COMP 329 Data Structures and Algorithm Analysis None 3
COMP 350 Database Concepts None 3
Core Courses (4 core course- 12 Credits)

These courses provide a breadth of foundational knowledge to implement computer interfaces, software design, communication between systems, and how to manage IT systems. These are all crucial elements for IT professionals to apply these building blocks to any given system or project.

Code Course Title Prerequisite Microcredentials Credits
COMP 501 Advanced Operating Systems COMP 260 3
COMP 502 Design and Analysis of Algorithms COMP 329 3
COMP 503 Networking and Telecommunications COMP 270 3
COMP 504 Database Management Systems COMP 350 3
Application Courses (2 Courses – 6 Credits)

These courses offer an opportunity for students to apply what they have learned throughout the program to a practical project or to a master’s thesis. While the practical project provides for application of knowledge acquired throughout the program and would be represent work that could demonstrate career-readiness to potential employers, the thesis would generally serve to demonstrate a student’s research potential and could be used to demonstrate readiness for doctoral work. Regardless of the option, students will demonstrate basic research knowledge and abilities, which would be used toward completion of either the project or thesis.

Code Course Title Prerequisite Microcredentials Credits
COMP 505 Research Methods None 3
Choose One of the Following
COMP 682 Data Analytics Capstone Project COMP 505 3
COMP 698 Master Thesis COMP 505 3
Specialization Courses (Any 6 Courses – 18 Credits)

These advanced courses cover the depth of topics related to Data Analytics and allow students to develop their knowledge based upon their intended professional trajectories.

Code Course Title Prerequisite Microcredentials Credits
COMP 523 Big Data Principles COMP 504 DA/BDA 3
COMP 524 Metadata Applications in Complex Big Data Problems COMP 504 PDS/BDA/BAE 3
COMP 525 Role of Analytics in Decision-making None DA/PDS/BAE 3
COMP 528 Data Analytics Foundation None DA/BDA 3
COMP 529 Information Fusion None BDA 3
COMP 531 Algorithms for Data Analytics COMP 329 BDA 3
COMP 542 Numerical Analysis   3
COMP 543 Data-Intensive Distributed Computing   3
COMP 544 Special Topics in Data Science None 3
COMP 596 Internship I in Data Analysis Completion of core courses and 50% of the program courses 3
COMP 626 Web Analytics None DWE 3
COMP 627 Descriptive and Predictive Analytical Tools COMP 528 DWE 3
COMP 628 Special Topics in Data Analytics None 3
COMP 629 Privacy and Security in Big Data None BDA 3
COMP 630 Text Analytics COMP 504 PDS 3
COMP 631 Cloudera Certified Associate (CCA) Data Analyst None Cloudera Certification/BAE 3
COMP 632 Microsoft Certified Azure Data Scientist Associate None Microsoft Azure Certification/PDS 3
COMP 696 Internship II in Data Analysis COMP 596 3

NOTE: Students who wish to take a course that is offered by in another program may petition to do so to their advisor by providing justification for the relevance of the addition as part of their professional trajectory, their intended consulting project, and/or personal interest. A maximum of 2 courses from can be applied from another program.


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