Program Description

The Data Analytics Engineering (DAEN) Master of Science Program is a multidisciplinary program in the George Mason University College of Engineering and Computing. This program provides students with knowledge and experience across a broad range of data analytics algorithms, tools, and processes, and focuses on a flexible and broad set of courses to be used by graduates for solving a wide range of real-world problems.

The online program can potentially be completed in approximately two years and will provide the graduate with an expanded set of career options and opportunities.

Unique, Real-World Program

Faculty in the online master’s in data analytics program are dedicated to offering a career-focused program. They meet regularly with an industry-expert advisory committee to ensure coursework is rigorous and relevant.

The program addresses three types of data analytics engineering: a) data engineering; b) data architecture; and c) data analysis. The data engineering area of the program is focused on data conditioning required to fit data into specific data architectures and transform data to be exploitable. The data architecture area is focused creating frameworks that make data driven intelligence possible. The data analysis area is focused on creating repeatable means to draw key insight and signal from data. In your capstone course, you’ll create a functional team project and deliver a technical report and oral briefing at its completion.

The multidisciplinary curriculum includes coursework from several departments within the College of Engineering and Computing.

Learn In a Top-Ranked School

George Mason’s College of Engineering and Computing has worked with Big Data and cybersecurity for more than 25 years. It’s led by faculty with rich industry experience and connections who draw upon both to teach a proven, career-focused curriculum and make you a top competitor for the future data architect, scientist, or analyst role you prefer.

  • The 20 Best Schools to Study Big Data Analytics — TechRepublic, March 2016
  • Top 50 Best-Value, Big Data Graduate Programs — Value Colleges, 2018
  • Top 50 Best Online Master’s in Engineering Programs — U.S. News & World Report, 2023

Online Graduate Certificate Option

Take four courses in roughly 12 months to gain foundational knowledge in data analytics engineering. Concepts covered include:

  • Data, data quality, and large volumes of data
  • Data management and data mining
  • Modeling and model usage for making decisions
  • Statistical methods and visualization

If you decide later to pursue the online MS in Data Analytics Engineering degree, credits from the graduate certificate will apply. For more information on the Graduate Certificate in Data Analytics Engineering click here.

Application Deadline

The MS in Data Analytics Engineering online program accepts applications on a rolling basis and is currently accepting applications. Applicants should apply here.

Virtual Open House

The George Mason University faculty dedicates time throughout the year to hold interactive sessions online for those who want to learn more about the programs we offer. If you would like to find out more about what you can expect from an online MS in Data Analytics Engineering, visit our pre-recorded Virtual Open House and watch at your convenience. For information on upcoming sessions, please don’t hesitate to contact us.

Learning Online

Learning online in an asynchronous format means that you can complete your degree at times and in locations that are best for you. Avoid commute times or “traditional” classroom hours, so you can complete your degree and advance your career even if you travel for work, have kids at home, or keep a busy or non-traditional schedule.

Coursework is delivered through a variety of prepared video lessons, readings, or engagement-orientated learning tasks that you’ll complete by predefined dates, but this doesn’t mean you learn alone. You’ll participate in lively conversations with peers and faculty in discussion posts, and many students form study groups with peers.

You will be required to participate in synchronous meetings for your capstone course – DAEN 690. This course is 15 weeks long*, as opposed to the rest of the courses which are 8 weeks in duration. This course will require virtual class lectures once a week from either 4:30 PM-7:10 PM or 7:20 PM-10 PM EST**. The day of the week will be determined once enrolled in this course. Students will be expected to discuss this with their employers and let them know that they are required to attend these sessions – no exceptions. DAEN 690 will be taken in the last semester of the program.

Students will also be required to meet once a week, for up to an hour, with the DAEN Program capstone partner who proposed the project and to which they are assigned to for the course. These meetings occur outside the regular class lecture meeting time and are set based on the availability of the capstone partner. Once again, if this occurs during the workday, students will need to notify their employers of the mandatory attendance at that partner meeting.

*DAEN 690 taken in the summer is 12 weeks long.

**DAEN 690 taken in the summer requires virtual class lectures once a week from 5-8:30 PM EST.

Faculty act as mentors throughout your program to ensure you’re on the right path to meet your career goals. You’ll get to know them well by phone, video conferences, emails, and through their thought-provoking questions and commentary within the course.

On-Campus Program Available

The master’s in data analytics engineering is designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making. Topics cover data mining, information technology, statistical models, predictive analytics, optimization, risk analysis, and data visualization. Aimed at on-campus students who wish to become data scientists and analysts in finance, marketing, operations, business intelligence, and other information-intensive groups generating and consuming large amounts of data, the program also has wider applications, including concentrations in digital forensics, financial engineering, and business analytics. Learn more about the on-campus program.

Wiley University Services maintains this website in cooperation with George Mason University. Admissions standards and decisions, faculty and course instruction, tuition and fee rates, financial assistance, credit transferability, academic criteria for licensure, and the curriculum are the responsibility of the Institution and are subject to change. We aim to keep this site current and to correct errors brought to our attention. Education does not guarantee outcomes including but not limited to employment or future earnings potential. Learn more about Wiley University Services.

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Program Summary

100 Percent Online

Program: Data Analytics Engineering (MS)

Degree: MS

College/School: College of Engineering and Computing

Credits: 30 total

Who should apply?

This detailed, experiential program is best for professionals who want to create the systems and processes to harness Big Data from a raw format into actionable knowledge that can inform key decisions. They’ll take on roles with titles such as data architect, scientist, engineer, or analyst, ready to power strategic solutions with the right data. The ideal candidate will have strong math skills. While no specific undergraduate degree is required, a background in engineering, business, computer science, statistics, or information technology is desirable.

Why choose George Mason?

  • George Mason’s College of Engineering and Computing has worked with big data and cybersecurity for more than 25 years.
  • Top 100 Best Engineering Schools by U.S. News & World Report, 2023.
  • The program’s online format allows the best analytical professionals to learn and advance this science together.
  • You can earn your degree in as few as 2 years and be on your way to advancing to roles like data scientist, engineer, or analyst.
  • World-renowned faculty with industry experience teach a career-focused curriculum that provides deep conceptual and practical knowledge.

Program requirements for the online MS in Data Analytics Engineering program are subject to change.

Requirements: 30 total credit hours

  • 15 credits in required courses
  • 15 credits in elective courses
  • Required Course for Provisional Admits:
    • DAEN 500 – Data Analytics Foundation
      • Provides a foundation in data analytics from which the student will build. Focuses on a dataset where students will use analytics tools and apply statistical methodologies in order to extract information of value.
  • Core Courses:
    • AIT 580 – Big Data to Information 
    • CS 504 – Principles of Data Management and Mining 
    • OR 531 – Introduction to Analytics and Modeling 
    • STAT 515 – Applied Statistics and Visualization for Analytics 
    • DAEN 690 – Data Analytics Project
  • DAEN Elective Course: 
    • DAEN 698 – Independent Research 
      • Conduct a research project to be chosen and completed under guidance of a graduate faculty member that results in an acceptable technical report. Notes: No more than a total of three credits may be taken from within the DAEN program. 
  • IST Elective Courses: 
    • AIT 524 – Database Management Systems 
    • AIT 526 – Introduction to Natural Language Processing 
    • AIT 614 – Big Data Essentials 
    • AIT 622 – Determining Needs for Complex Big Data Systems 
    • AIT 624 – Knowledge Mining from Big-Data (Required Prerequisite: AIT 582) 
    • AIT 636 – Interpretable Machine Learning 
    • AIT 664 – Information Representation, Processing and Visualization (Recommended Prerequisite: AIT 524) 
    • AIT 726 – Natural Language Processing with Deep Learning (Prerequisite: AIT 526) 
    • AIT 736 – Applied Machine Learning 
    • AIT 746 – Applied Deep Learning (Prerequisite: AIT 636, AIT 736, & CS 504) 
  • SEOR Elective Courses: 
    • OR 568 – Applied Predictive Analytics (Recommended Prerequisite: STAT 515) *Spring 2024* 
    • SYST 542 – Decision Support Systems Engineering 
    • SYST 573 – Decision and Risk Analysis 
    • SYST 584 – Heterogeneous Data Fusion *Spring 2024* 
  • ECE Elective Courses: 
    • DFOR 510 – Digital Forensics Analysis *Spring 2024* 
    • DFOR 660 – Network Forensics  
  • GBUS Elective Courses (Students taking GBUS courses must be in enrolled in both the course and recitation sections): 
    • GBUS 721 – Marketing Research (a.k.a., MBA 721– Marketing Research)  
    • GBUS 739 –  Advanced Data Mining for Business Analytics (a.k.a., MBA 739 – Advanced Data Mining For Business Analytics)
      (Required Prerequisite: GBUS 738 – Data Mining for Business Analytics (a.k.a., MBA 738 – Data Mining for Business Analytics) 
    • GBUS 738 – Data Mining for Business Analytics (a.k.a., MBA 738 – Data Mining for Business Analytics) 
    • GBUS 720 – Marketing Analysis (a.k.a., MBA 720 – Marketing Analytics) 

Tuition & Fees (2024-2025):

Tuition is $930 per credit hour. An additional charge of $35 per credit hour applies for a distance education fee.

Financial Aid

For information on loans and scholarships, visit the Office of Student Financial Aid. For information regarding grants, tuition waivers and other merit aid, please inquire with your graduate department.

The online MS in Data Analytics Engineering program combines strong foundational concepts with deep technical savvy and plenty of hands on experience so you can choose how you work with Big Data as you advance your career.

You’re Ready To:

  • Create the framework that makes data-driven intelligence possible as a data architect/scientist.
  • Condition data to fit into a framework and make it exploitable as a data engineer.
  • Repeatedly draw key insights from data and use them in business strategies as a data analyst.
  • Find work in private, government, profit, and non-profit sectors.
  • Work within information-science-technology, systems engineering, and statistic industries.

Data Scientist vs. Data Analyst Titles

Though the titles can often share or overlap responsibilities, and are sometimes used to mean the same thing, in the strictest definitions, data scientists and data analysts are different roles. Mason’s online master’s in Data Analytics Engineering prepares you for both.

  • Data Scientists design the systems for handling data. They have a strong background in computer science and experience in building systems.
  • Data Analysts are generally subject matter experts. They have input into the systems that are designed, but their job is to mine the systems and leverage them to produce actionable strategy.

If you are unable to find the answers to your questions, submit a Request For Information form or contact our admissions representative via the contact information below.

Phone: 703-348-5006

How do I apply?

Applicants should apply here.


Can I take courses without applying?

Only students who are admitted to the Master of Science in Data Analytics Engineering program may take classes in the program.

What are the requirements for admission?

Applicants must have completed a baccalaureate degree from a regionally accredited program with an earned GPA of 3.00 or better in their 60 highest-level credits. Applicants are expected to have completed a degree in engineering, business, computer science, statistics, mathematics, or information technology, with demonstrated foundational competence in calculus, statistics, and computer programming. Applicants without that formal academic preparation but with clear evidence of strong and extensive work experience in data or analytics, may also be considered on a case by case basis.

In addition to fulfilling George Mason’s admission requirements for graduate study, applicants must provide:

  • Completed online application
  • $75 application fee
  • Undergrad GPA-minimum 3.0 (submit all undergraduate and graduate transcripts)
  • GPA Addendum essay if undergrad GPA below 3.0
  • A letter of recommendation, preferably from an academic reference or reference in industry or government who is familiar with the applicant’s professional or academic accomplishments
  • Resume
  • Detailed statement of career goals and professional aspirations
  • If the applicant’s native language is not English, proof of English competency with a minimum TOEFL score of 575 for the paper-based exam or 230 for the computer-based exam

Is a GRE/ GMAT required?

Neither the GRE nor the GMAT is required for admissions.

How long does it take to complete the program?

The online MS in Data Analytics Engineering degree is 30 credit hours and can be completed in as few as 2 years.

When are classes held?

Online classes are offered in an asynchronous format, meaning they can be viewed interactively at your convenience. However, students still must meet all study and deliverable requirements and deadlines.

What is an asynchronous format?

Learning online in an asynchronous format means that you can complete your degree in the times and locations that are best for you.

Coursework is delivered through a variety of prerecorded video lessons, readings, or game-based learning tasks that you’ll complete according to the due dates in the syllabus, but this doesn’t mean you learn alone. Instead, you’ll get to know faculty and your peers in discussion posts, study groups, online chats, and video conferences when everyone logs in at the same time to hold discussions and work together.

What accreditation does George Mason hold?

George Mason University is accredited by the Commission on Colleges of the Southern Association of Colleges and Schools to award bachelors, masters and doctoral degrees.

How much does it cost to apply?

While there is a $75 application fee, there are multiple times throughout the year that it may be waived.