Building Shared Data Infrastructure for School-Based Nonprofits

A key strength of the American K-12 education ecosystem is the tens of thousands of nonprofit organizations working inside schools to help students attend more regularly, stay on track academically, build stronger relationships with adults, and access the support they need to thrive. These organizations often bring deep trust, specialized programming, and additional capacity to schools. But many of these organizations are trying to do modern, evidence-informed work with data systems that were not designed for them.

Individual nonprofits should not have to solve this as a technical problem one district at a time. The deeper challenge is public-good infrastructure: schools, districts, nonprofits, funders, researchers, and public agencies all need secure, timely, well-governed pathways for using education data responsibly.

A large school-based nonprofit may operate across dozens of districts, hundreds of schools, and multiple states. Its staff may need to know, week by week, which students are chronically absent, which students have improving or declining course performance, and which classrooms or grade levels need additional support. At the same time, nonprofit leaders need to evaluate impact, report to funders and public agencies, support compliance requirements, launch new sites, and learn across regions.

Those are not the same data needs. But today, they are often forced through the same resource-intensive process: request a custom file from each district, wait for it to arrive, clean and interpret it locally, and then try to make it useful before the information is already stale.

When we talk with school-based nonprofit partners, we hear a consistent concern: the data they need to support students, learn across sites, and demonstrate impact often arrives too late, in too many formats, and with too much local interpretation required. City Year, a national education nonprofit whose AmeriCorps members serve as student success coaches in schools across 29 U.S. cities, describes this as a shared infrastructure problem rather than a single-organization challenge.

As Stephanie Wu, City Year’s chief transformational officer, put it: “We all are committed to improve and innovate, yet we each use a different data picture, which dilutes our collective impact due to a lack of shared measures and insights.”

District data teams are also operating under real capacity constraints. Even with strong intentions on both sides, data exchange between districts and nonprofit partners can become slow, manual, and incomplete when there is no common infrastructure for collecting, cleaning, governing, and sharing approved data.

Two data jobs, one shared challenge

For school-based nonprofits, data needs tend to fall into two broad categories.

The first category is local operational data. This is the information that site staff and program leaders need to make day-to-day decisions in schools. It supports questions like:

• Which students may need additional attendance support this week?
• Which students should be prioritized for tutoring, mentoring, or near-peer coaching?
• Are interventions reaching the students they were designed to reach?
• Are there differences across schools, grades, or student groups that should change how support is assigned?
• Are staff seeing the same patterns that appear in the data?

These data must be timely, actionable, and close to on-the-ground practice. They do not need to answer every research question. In fact, data collected for operational decisions are often not well suited, by themselves, for research or evaluation. Their primary job is to help school-based teams make better near-term decisions with the students in front of them.

The second category is central learning, reporting, and evaluation data. This is the information that district headquarters and non-profit national offices need to understand whether programs are working, where implementation is strong or uneven, how outcomes differ across contexts, and what should be improved. It supports questions like:

• What patterns are we seeing across sites?
• How are attendance, grades, behavior, or assessment outcomes changing for students served by the program?
• What do funders, national offices, boards, and public partners need to understand about reach, quality, and results?
• What data is needed to set up a new site responsibly?
• What can researchers learn across districts without reinventing the data pipeline every time?

This kind of data must be consistent, well-governed, and research-ready. It needs enough standardization to support comparison, yet enough context to avoid overgeneralizing across local differences.

Large school-based nonprofits need both kinds of data. Local teams on the ground need data for continuous improvement and student support. Central teams need data for learning, measurement, reporting, and organizational decision-making. When those needs are handled separately, organizations often end up with duplicated work, inconsistent definitions, and new reporting burdens.

Why the current approach breaks down

In many places, the default data-sharing model still depends on custom, static files. A nonprofit negotiates a data-sharing agreement with a district. A district data team prepares extracts from the student information system or other source systems. The nonprofit receives files on a schedule that may or may not match the pace of day-to-day student support work in schools. Then someone at the nonprofit, often with limited data infrastructure support, has to clean, map, validate, and interpret those files.

That process can work once. It can sometimes work for a small number of districts. It does not work well on a national scale.

The problem is not simply that custom files are inconvenient. It is that each custom file creates a new miniature data system. Definitions vary. File layouts change. Student identifiers must be reconciled. Attendance codes may mean different things in different places. Course grades may be stored differently across systems. Staff have to remember which district sends what, when, and in what format.

The result is that data access becomes a bottleneck. Local nonprofit staff may not get information quickly enough to support students in real time. Central office teams may spend more time assembling data than learning from it. Districts receive repeated, bespoke data requests from multiple partners. Researchers may narrow their questions because the data work is too expensive or too slow.

When that happens, everyone loses. City Year’s experience shows what this looks like in practice: even sophisticated nonprofit partners often have to supplement incomplete or delayed student data with other sources, such as staff or member surveys, because the current exchange model was not built for timely operational learning or rigorous cross-site evaluation. 

Case study: City Year

City Year’s Education Research & Strategy Team has worked to strengthen the data it uses to understand the impact of City Year AmeriCorps members on students and schools, as well as AmeriCorps members’ own growth and development as student success coaches. That information is critical for the continuous improvement of City Year’s services, training, and partnerships, and for supporting stronger outcomes for both students and corps members.

Recognizing a need to more closely understand the experience of serving in schools, City Year partnered with Culture Amp to create a survey that tracks AmeriCorps members’ experiences and leadership development over the school year, says Kris De Pedro, who leads City Year’s research strategy.

The survey illustrates the tension this blog post is describing: one source of data can support near-term operational learning about the service experience, while also contributing to longer-term research, evaluation, and funder reporting.

The AmeriCorps member survey helps City Year understand the service experience and member development. But it cannot, on its own, provide the consistent and timely student-level information needed to understand academic performance, social and emotional growth, attendance, and the conditions in schools where services are delivered.

A more robust data-sharing system would also help to capture the complex, multifaceted kinds of work that happen in schools today. For example, in schools and communities experiencing systemic underinvestment, City Year may be the only nonprofit partner working in a particular school; in other settings, City Year may be one of several nonprofits offering different supports. Shared infrastructure cannot remove all of the complexity of measuring program impact, but it can make that work more credible and less burdensome. When program participation, student outcomes, timing, school context, and other supports are defined consistently and documented in the same governed environment, nonprofits and districts can better understand what changed, for whom, under what conditions, and alongside which other services.

“A shared data infrastructure would enable cross-organizational collaboration to support students day-to-day and also to better understand our unique impact on students,” said De Pedro.

Common infrastructure changes the operating model

A better approach is to treat data access for school-based nonprofit work as a shared infrastructure challenge. As part of the Ed-Fi Alliance, the Ed-Tech Collaboratory, and other community members, EA works with districts and their partners to create the governed, repeatable data pathways that make shared infrastructure possible.

A common data infrastructure does not mean one giant database that erases local context. It means a governed, repeatable way to move core education data from the systems that already manage it into formats that authorized partners can use safely and consistently. Ed-Fi, a widely adopted, open-source data standard for K–12 education, can provide a common language for this work. When districts and nonprofit partners work from shared definitions for attendance, enrollment, grades, and student demographics, the data-sharing burden drops significantly, and the work of organizations like City Year becomes easier to support, evaluate, and scale.

At its best, common infrastructure does four things.

What this looks like in practice

For a large school-based nonprofit, common data infrastructure might support two connected but separately governed data surfaces.

One surface is designed for school and site operations. It might show authorized staff which students are newly off track for attendance, which students have changed risk status, which students are receiving which supports, and where staff follow-up is needed. This surface should be easy to use, role-aware, and grounded in the rhythms of school teams. Its purpose is coordinated support.

The other surface is designed for organizational learning and reporting. It might support program dashboards, funder reporting, parent organization reporting, board updates, evaluation datasets, new-site planning, and research partnerships. This surface should emphasize clear definitions, reproducible measures, data quality checks, and appropriate aggregation or de-identification.

The same underlying infrastructure can support both surfaces. Local action and central learning should not require two disconnected data worlds. They can use a common, secure, privacy-preserving infrastructure with access governed and audited for different purposes. For instance, in EA’s product ecosystem, Stadium provides managed warehouse infrastructure for consistent, well-governed data at scale; Podium supports leader-facing visualization and reporting; and Rally supports practitioner-facing views designed for timely student support—and all three use a common interoperable standardized data source.

When the infrastructure is shared, the same underlying data world can support different use cases without forcing every use into the same static flat file. A student support indicator used by site staff can be tied to the same definitions used in central reporting, while still appearing in a workflow designed for local action. Researchers can work from governed, documented datasets rather than one-off extracts. Program leaders can see where implementation differences may explain outcome differences. A new site can start with known data requirements instead of inventing them from scratch.

Shared infrastructure is not just technology. It also requires governance, support, and trust. Districts need confidence that access is appropriate and auditable. Nonprofits need clear definitions and timely support when data do not look right. Schools need to know that data will be used to improve adult decisions and student supports, not to label students as problems. Without those conditions, even a technically sound system will not produce shared learning.

A public-good approach

The education sector does not need every nonprofit, researcher, and district to build separate data plumbing for the same basic information. That approach is expensive, slow, and inequitable. Organizations with more technical capacity get better data. Smaller organizations, rural communities, and under-resourced districts are left with manual workarounds.

A public-good approach asks a different question: What parts of the data infrastructure should be shared, standardized, and reusable so that more organizations can focus on serving students

That does not mean every tool should be the same. Local communities need flexibility. Programs need room to adapt. Researchers need different designs for different questions. But the underlying pathways for secure, timely, well-governed data access should not have to be reinvented for every partnership.

The opportunity ahead

Large school-based nonprofits are one place where the field’s next-generation data infrastructure needs are becoming especially visible. They need timely operational data for site-level decisions. They need consistent vertical reporting for national learning, compliance, evaluation, and growth. They need systems that respect district governance and reduce burden rather than adding new demands.

If we, as a sector, can build that kind of infrastructure, the payoff is bigger than any single organization. Districts can work with partners more safely and efficiently. Nonprofits can target support and learn faster. Researchers can ask stronger questions. Funders can understand impact with more confidence. Students can benefit from adults who are better coordinated, better informed, and better able to respond.

While the work isn't simple, the path to completing it is becoming clear: common standards, governed access, reusable data models, local action tools, central learning systems, and a commitment to public-good infrastructure over proprietary lock-in. Though overlapping with state reporting and compliance challenges, this is really a shared movement that requires everyone who generates, stewards, and uses education data—including school-based nonprofits—to help shape the infrastructure, governance, and trust conditions that make responsible data use possible.

For school-based nonprofits, better data infrastructure is part of what makes high-quality, equitable student support possible at scale. Education Analytics is committed to building and stewarding that infrastructure as a nonprofit partner focused on open standards, public-good tools, and agency control of data. We work with districts, states, and partner organizations to make responsible data use easier, safer, and more useful for the people supporting students every day.

Case study: Data challenges

In some sites, City Year data analysts are facing steep challenges with data, reporting difficulty with connecting with school districts, delays receiving student performance data, or receiving information so late in the school year, it’s not useful anymore.

Case study: Data in action

While receiving processed data from school partners continues to be a challenge, Ash said that her school partners have been “instrumental in supporting our efforts by providing as much raw data as possible. This allows us to facilitate targeted trainings, develop meaningful resources, and equip our AmeriCorps members with the information they need to excel in both their student academic interventions and whole child initiatives.”

The work ahead is not simple, and the direction is clear. Common standards, governed access, reusable data models, and a commitment to public-good infrastructure make responsible data use possible at scale. For school-based nonprofits, this is part of what equitable, high-quality student support requires.