Mason OnlineProgram 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, 2025
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.
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