The Challenge
A global automotive manufacturer's quality analytics infrastructure had become a bottleneck. Centralised data ownership created dependencies, delayed reporting, and made it difficult for distributed teams to access the quality data they needed to make timely decisions.
The Solution
We implemented a Data Mesh architecture to decentralise data ownership across the organisation, enabling individual domains to own, publish, and govern their data as products. The platform was built on PySpark and OpenShift, with Argo CI/CD and Bamboo CI for automated deployment, Helm for infrastructure management, and Grafana and Kibana for observability — powering both the eSQA and SQACore quality analytics platforms.
The Impact
Quality data is now decentralised, scalable, and consistently available to every team that needs it. The two core platforms — eSQA and SQACore — operate on a unified, reliable data foundation with full observability and automated delivery pipelines.
Reflection Question: Is your data architecture enabling your teams or slowing them down? What would decentralised data ownership unlock for your quality operations?
Let's discuss how a Data Mesh approach could transform your data infrastructure.