Illuminations and Insights

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. In this blog, Vice President of Strategic Philanthropy and Innovation Dan Jarratt describes this shared infrastructure problem, uses City Year's work as a case study in strengthening data infrastructure, and highlights how Education Analytics (EA) is committed to building and stewarding that infrastructure.

At the start of 2026, Education Analytics (EA) closed out a five-year grant that became one of the most formative chapters in EA’s history. The work — supporting six Networks for School Improvement (NSIs) across California through the Bill & Melinda Gates Foundation — pioneered infrastructure that helped shape many of the products that EA builds today. Services Delivery Lead Brianna Pollari and Senior Technical Program Manager of Data Science Drew McDermott, who were heavily involved in NSI work, describe the challenges and triumphs of building this infrastructure in this blog.

Enable Data Union (EDU) is now compatible with Databricks. EDU was built on the principle that shared data infrastructure for public education should be open, standards-based, and never locked to a single vendor. When the Tennessee Department of Education told us their environment ran on Microsoft and Databricks — and switching wasn't an option — we saw an opportunity to prove that open, vendor-neutral infrastructure was possible. Thanks to a close collaboration with Tennessee's team, including direct code contributions, EDU now runs on Databricks. One state's contribution becomes a starting point for every agency that comes after them. Technical Lead Manager Rob Little shares the full story in this blog.

In this blog, CEO Andrew Rice reflects on the new vision document from the Institute of Education Sciences (IES), Reimagining the Institute of Education Sciences. In the blog, Andrew shares how strongly the vision resonates with the work EA's been building toward for years—especially the call to move education data from a static snapshot to a continuous stream. Real modernization requires shared, durable software. It requires governance, engineering capacity, and cross-state collaboration through models like state consortia. It requires equipping researchers with data engineering skills alongside statistical expertise. Andrew reflects on what it will actually take to make the IES vision a reality—and why this moment matters.

Co-hosts of the DatabasED Podcast, Senior Product Manager Molly Stewart and Vice President of Product Rosh Dhanawade, recently interviewed Principal Researcher Michael Christian and Research Scientist I Sara Hu about how interoperability has changed their research work at Education Analytics (EA). This blog includes highlights from their episode.

K-12 has lived through many “next big things” in edtech. Some have delivered real value, especially in large-scale data collection and adaptive learning. But across states and districts, student outcome progress and gaps remain stubborn, and leaders are rightly skeptical that a new wave of AI tools alone will change that. This is not simply a failure of technology. It reflects a basic fact: no algorithm can solve challenges rooted in resource inequities or social conditions. What AI can do is help educators, policymakers, and researchers reason more clearly with the information they already have. That only works if the data are accurate, standardized, and connected, and if the people closest to students remain in charge of how those data are used. In this blog, Vice President of Data Science Dan Jarratt discusses how, in order to ensure that AI systems that are effective, auditable, and equitable for students, we must start with something more basic: open, interoperable, standardized data infrastructure that public agencies can govern and sustain.