This last-mile perspective transforms anomaly detection from a data quality tool into a strategic business capability. So, instead of just catching errors, it becomes a tool for validating the business's narrative across all data domains

What's becoming increasingly clear is that active metadata isn't just another tool in the modern data stack – it's a key enabler of several contemporary data management strategies.

Imagine a simple, standardized, data-source-agnostic data quality service that could complement existing approaches and dramatically improve data health through rapid feedback loops.

GraphQL and OpenAPI define agreements between data consumers and providers, but they have significant differences in capabilities and contract specifications. Whichever you use, it's essential to be intentional, understand your use case, and design for the best outcome.

Leveraging the supergraph architecture to achieve data governance objectives is a strategic play that delivers a solid return on investment. It reduces complexity, lowers costs, and improves metadata accuracy.