2026 Best Value Data Processing Schools in District of Columbia

[Data Processing](/majors/computer-information-sciences/data-processing/) programs reward a close look at where your money goes furthest. A high-value program keeps cost low while graduates go on to earn well.
College Factual analyzed 2 schools to build this 2026 ranking of the best value data processing schools.
What’s on this page:
2026 Best Value Data Processing Schools in District of Columbia
Below are the schools that deliver the strongest value in data processing, balancing cost against outcomes.
Best Value Data Processing Schools
Leading the list is George Washington University, our #1 best value for data processing in District of Columbia. George Washington University is a very large private not-for-profit school located in the city of Washington. Expect in-state tuition and fees of around $67,710. Typical student debt for data processing graduates is $22,910. Soon after graduation, data processing degree recipients from George Washington University generally make around $73,749. That is a strong return on a $22,910 median debt. The acceptance rate is 47%.
More Data Processing Rankings
View All Data Processing Rankings >
Notes and References
The ranking above is published by College Factual (MF_RANKING_2025), 2026 edition. Schools are scored on the balance of cost (tuition and student debt) against student outcomes (post-graduation earnings) — a measure of return on investment, drawn primarily from the U.S. Department of Education (IPEDS and College Scorecard).
Ranking method: College Major Best Value · 2 schools evaluated.
*Averages shown above reflect the top 1 ranked schools 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.