2027 Best Value Data Processing Technology Schools in District of Columbia
[Data Processing Technology](/majors/computer-information-sciences/data-processing/data-processing-tech/) programs reward a close look at where your money goes furthest. The best values balance affordable tuition against strong post-graduation earnings.
For its 2027 best-value ranking, College Factual looked at 1 schools to find the best return on investment for data processing technology students.
What’s on this page:
2027 Best Value Data Processing Technology Schools in District of Columbia
If you want to know which schools deliver the best value for the data processing technology degrees they offer, see the list below.
Best Value Data Processing Technology Schools
Leading the list is George Washington University, our #1 best value for data processing technology in District of Columbia. Set in the city of Washington, George Washington University is a very large private not-for-profit institution. Expect in-state tuition and fees of around $67,710. Data Processing Technology graduates carry a median of $22,910 in student loans. Early-career data processing technology graduates make about $73,749. That is a strong return on a $22,910 median debt. Roughly 47% of applicants are accepted.
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Notes and References
The ranking above is published by College Factual (MF_RANKING_2025), 2027 edition. The methodology weighs the cost of a degree against the earnings graduates go on to achieve, drawn primarily from the U.S. Department of Education (IPEDS and College Scorecard).
Ranking method: College Major Best Value · 1 school evaluated.
*Averages shown above reflect the one ranked school only.
- The Integrated Postsecondary Education Data System (IPEDS) from the National Center for Education Statistics (NCES), a branch of the U.S. Department of Education (DOE), serves as the core of our data about colleges.
- Some other college data, including much of the graduate earnings data, comes from the U.S. Department of Education’s (College Scorecard).
More about our data sources and methodologies.
