Governed Lakehouse Architecture: Leveraging Databricks Unity Catalog for Scalable, Secure Data Mesh Implementation (International Journal of Engineering & Extended Technologies Research (IJEETR), 2023)
The trajectory of enterprise data architecture has long been defined by a dialectical tension between the rigid order of the warehouse and the scalable anarchy of the data lake, a cycle currently manifesting in the sociologically seductive but technically immature concept of the Data Mesh. While the existing literature privileges the organizational benefits of domain ownership relying heavily on "gray literature" and blog posts rather than rigorous academic scrutiny it remains dangerously silent on the engineering mechanics required to prevent governance fragmentation. This study operationalizes the "Governed Lakehouse" architecture, utilizing a Federated Data Insights Platform to enforce global invariants security, semantic federation, and auditability across a heterogeneous environment. By acknowledging the fundamental distinction between global schema (presentation) and local schemas (storage), the proposed architecture replaces ad-hoc provisioning with a structured mediation mechanism. However, our analysis indicates that while this control plane successfully enforces syntactic interoperability, true integration requires semantic enrichment to bridge disparate systems. Ultimately, this research demonstrates that a viable Data Mesh is not merely a decentralized organizational model but requires a rigid, centralized metadata substrate specifically, a Minimal Lakehouse Architecture to function, redefining governance not as a bureaucratic gatekeeper but as a computed property of the infrastructure itself.
Keywords: Data Mesh; Governed Lakehouse Architecture; Federated Data Ecosystems; Enterprise Architecture; Domain-Driven Design; Semantic Federation; Metadata Management; FAIR Principles