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Global Education Provider

Unifying Millions of Student Data Points in just 9 Weeks

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Summary:

Our client is a global education provider with tens of thousands of employees and a presence across multiple continents. They support millions of learners preparing for high-stakes professional and academic exams. Their business model is built on student success. Many of their courses include score guarantees. If students do not achieve the required results, refunds may apply. This makes early visibility into student performance critical not just for learning outcomes but for protecting revenue. However, student information was spread across multiple systems. Each platform tracked different parts of the learner journey. There was no single view of performance, engagement, or risk.

Tech Stack:

  • Cloud & Database: MongoDB Atlas
  • Message Broker: Apache Kafka
  • Change Data Capture: Debezium, Kafka Connect, MongoDB Kafka Connector
  • Stream Processing: Apache Flink 1.18 (PyFlink — Python API)
  • Data Modeling: YAML-driven mapping engine, Pydantic data models
  • Observability: structlog, Kafka UI
  • Infrastructure: Docker, Docker Compose
  • Testing: pytest

A global education provider partnered with gravity9 to solve a growing visibility problem across millions of learner data points spread across multiple disconnected systems. With no unified view of learner progress, engagement, or risk, the organisation needed a faster and more intelligent way to identify struggling students early, protect outcomes, and maintain strict refund targets.

gravity9 designed and delivered a unified real time data platform in just nine weeks, connecting fragmented sources, aligning learner identities, and generating live risk scores teams could act on immediately. The result was a scalable foundation that gave the client a single view of each learner, enabled earlier intervention, improved operational responsiveness, and created a strong base for future AI driven personalisation.

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