Schoolytics Enhances Student Outcomes with Embedded Analytics and AI Insights

Schoolytics is a purpose-built data platform that is specifically designed to bring together fragmented educational data sources. Their goal is to reduce the burden of data management on school staff so they could spend more time driving better educational outcomes, such as improving student attendance, grades, assessment scores, and homework trends.

When Co-founder and CEO Aaron Wertman started Schoolytics in 2020, he had a clear vision to empower school districts with data-driven insights for better educational outcomes without needing large engineering teams. His prior experience as a data scientist at Chegg and countless conversations with educators reinforced one critical insight: K-12 schools have abundant data but often lack capacity to make it actionable.

Early Success and Growing Pains

Initially, Schoolytics built a custom embedded analytics solution from the ground up with a mix of tools and writing their own frameworks. This solution integrated with multiple systems, including Student Information Systems (SIS), Learning Management Systems (LMS), and assessment platforms, storing data primarily in Google BigQuery. The early versions were functional but quickly reached limitations.

Aaron and his team realized they were continually reinventing the wheel, repeatedly constructing common data modeling patterns for dimensions and measures. The custom-built semantic layer they unintentionally created was increasingly difficult to scale, maintain, and customize. “We were clearly building a semantic layer, but it felt hacked together,” Aaron recalls. “We needed something robust, scalable, and flexible.”

Schoolytics explored several solutions, including open source frameworks and popular BI platforms like Looker, Tableau, and Metabase for embedded analytics. However, none provided the composability and cost-effectiveness they needed. They required a seamless, customizable embedded experience for their end users. This was a non-negotiable requirement for executing on Schoolytics’ vision for a distinct brand and user experience.

Rapid Wins with New Challenges

In 2021, a friend introduced Aaron to Cube Core. They were really impressed with how easy it was to work in Cube’s centralized repository, define the data model, and hook it up to their embedded analytics solution. Immediately, Schoolytics experienced dramatic improvements, unlocking customer-specific data models.

Cube’s universal semantic layer, combined with its intuitive syntax, robust data modeling, and pre-built query caching, became foundational for the Schoolytics platform. It enabled them to quickly integrate diverse data sources and maintain a composable and customizable experience.

Scaling their self-hosted Cube Core environment became a significant challenge. At the time, Cube Core used Redis for caching, which was prior to the advancements made with the release of Cube Store for the in-memory cache. Cube Core with Redis caching became hard to manage.

According to Wertman, they continually faced challenges in managing a growing multi-tenant environment, attempting to auto-scale the platform, and handling increasingly complex customizations. Schoolytics was starting to spend more time managing infrastructure than building features.

From Infrastructure Challenges to AI-Driven Innovation

The resource burden on the small team prompted them to migrate to Cube Cloud as they’ve grown, now supporting 60-plus school districts nationwide today. Cube Cloud offered Schoolytics exactly what they needed in managed infrastructure, effortless scalability, and reliable pre-aggregations. The migration from their self-managed Cube Core deployment to Cube Cloud dramatically improved stability, concurrency, and performance at scale.

“Pre-aggregations became huge for us,” Aaron explains. “As our customer base grew and the complexity of our data increased, the ability to precompute insights across tens of thousands of students and dozens of dimensions dramatically improved performance. Queries that once took minutes now execute in seconds.”

Beyond performance, Cube Cloud also radically changed Schoolytics’ operational workflow. Before Cube Cloud, updating their semantic layer required engineers to write code, run deployments, and carefully manage each release, often taking 15 minutes or more per update.

With Cube Cloud, any analyst can now handle data model changes, completing deployments in just seconds. This shift has freed engineering resources to focus on high-value tasks, driving innovation and efficiency across the board. “It’s a massive productivity gain. Now, the analysts are not dependent on engineers to safely and quickly deploy changes, saving us significant time and resources,” Aaron notes.

“Cube became the bones—the core foundation—of Schoolytic’s embedded analytics and AI,” he explained. “It’s what makes our platform consistently deliver accurate, timely embedded analytics and AI-driven insights back to the schools.”

– Aaron Wertman, Co-Founder & CEO, Schoolytics

Schoolytics uses one base set of cubes for every school district, and then they built a custom framework that’s pretty unique. Their multi-tenant setup allows individual school districts to customize and extend the base data models directly in a custom-built editor integrated with Cube’s API, thanks to Cube’s flexible data modeling capabilities. In a similar fashion to modeling in Cube Cloud, they've built a lightweight version of that in Schoolytics so every customer can edit their own cubes.

Cube Cloud has also helped position Schoolytics as a leader in AI-driven educational insights. Schoolytics now offers a custom AI-powered assistant into their platform, leveraging Cube’s semantic modeling to provide context for trusted automated insights and intuitive data exploration for educators. Aaron says it would have been daunting without Cube’s structured approach to make their data AI-ready from the start.

Expanding the Vision and Amplifying Impact

Schoolytics has scaled to support over 60 school districts across the nation. Looking forward, Schoolytics is eager to expand its use of Cube Cloud and enhance its data modeling capabilities with AI-assisted cube generation. Aaron emphasizes, “Cube’s semantic layer isn’t just nice-to-have—it’s absolutely central. It ensures the factual accuracy and usability of our entire platform. We couldn’t operate without it.”

Schoolytics sees Cube as an essential partner, helping them deliver consistent, reliable, and insightful data to educators nationwide. “We’re huge Cube fans,” Aaron concludes. “It’s reliable, durable, and scalable. Cube Cloud makes our mission possible.”