Finding the Best Value Data Visualization School for You
The right data visualization school can pay off for years to come. To help, we created our Best Value Data Visualization Schools ranking. It weighs the cost of a degree against the outcomes graduates go on to achieve, so you can find the strongest return on your investment.
Read more about our methodology
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We offer a number of rankings, including this Best Value Data Visualization Schools list, to help you decide. More interested in schools in a specific area of the country? Filter this list by region or state.
To further help you make the college decision, we have developed a unique tool called College Combat that lets you compare schools on the factors that matter most to you.
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2026 Best Value Data Visualization Schools in the United States
If you want to know which schools deliver the best value for the data visualization degrees they offer, see the list below.
Best Value Data Visualization Schools
University Of Washington Bothell Campus earned the #1 spot for value among data visualization schools in the United States. Located in the suburb of Bothell, University Of Washington Bothell Campus is a moderately-sized public university. Students from in state pay about $12,919 in tuition and fees, compared with $43,155 for out-of-state students. Typical student debt for data visualization graduates is $15,636. Data Visualization graduates of University Of Washington Bothell Campus earn a median of $65,932 early in their careers. That is a strong return on a $15,636 median debt. The acceptance rate is 91%.
The strong cost-to-outcome balance at New Jersey Institute Of Technology earned it the #2 place for data visualization. Located in the city of Newark, New Jersey Institute Of Technology is a large public university. In-state tuition and fees average $19,974, compared with $37,664 for out-of-state students. Typical student debt for data visualization graduates is $24,755. Data Visualization graduates of New Jersey Institute Of Technology earn a median of $71,549 early in their careers. Set against $24,755 in median debt, that is a healthy payoff. The acceptance rate is 65%.
Students looking for strong value in data visualization will find it at University Of South Carolina Columbia, which ranked #3. Located in the city of Columbia, University Of South Carolina Columbia is a very large public university. Expect in-state tuition and fees of around $12,688, with out-of-state students paying around $36,298. Data Visualization graduates carry a median of $24,472 in student loans. Early-career data visualization graduates make about $54,087. That is a strong return on a $24,472 median debt. University Of South Carolina Columbia admits about 60% of applicants.
The strong cost-to-outcome balance at Carnegie Mellon University earned it the #4 place for data visualization. Set in the city of Pittsburgh, Carnegie Mellon University is a large private not-for-profit institution. The average in-state cost of tuition and fees is $65,636. Typical student debt for data visualization graduates is $23,529. Soon after graduation, data visualization degree recipients from Carnegie Mellon University generally make around $89,327. Weighed against typical debt, the earnings make a compelling case for value. Roughly 12% of applicants are accepted.
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Notes and References
This list is compiled by College Factual (MF_RANKING_2025), 2026 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 · 8 schools evaluated.
*Averages shown above reflect the top 2 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.