Frontend-Driven Metadata Governance: A Full-Stack Architecture for High-Quality Analytics and Privacy Assurance
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V2I3P111Keywords:
Frontend Metadata Governance, Full-Stack Analytics Architecture, Data Quality Assurance, Privacy-First Event Tracking, Client-Side Metadata Intelligence, Enterprise Analytics Compliance, Semantic Event GovernanceAbstract
To maintain superior quality of analytics and protect the privacy of individuals, then metadata must be exact, comprehensive and regulated in all levels of the data life cycle. Conventional metadata governance systems are based on mostly backend enforcement, and therefore they have delayed validation, did not capture metadata in a consistent manner and had quality gaps every time a new data is generated. This paper presents a metadata governance paradigm that is frontend-based, and that implements metadata capture, validation and privacy enforcement directly into user-facing applications. The architecture provides real time lineage tagging with schema based signature-driven UI elements, policy constrained form generators and a minimum number of user friction. Resources included in the model are a lightweight frontend governance SDK, which links to one middle tier comprised of a policy orchestrator and a backend metadata repository that supports versioning, lineage tracking, and compliance auditors.
A committed privacy assurance engine implements controlling principles such as verification of consent, restriction of purpose and personalization of the data in accordance with GDPR, CPRA, and further developing global laws. Experimental findings indicate that this approach of a frontend-based methodology raises completeness of metadata, consistency by 38 and 32 percent, and accuracy of privacy compliance by 41 percent compared to using backend-based strategies only. The large retail analytics ecosystem Architecture has been validated as a production deployment with sub-50 ms end-to-end validation latency and throughput making millions of metadata events per day. On the whole, this work makes the following contribution: (1) a new paradigm of governing the origin of data creation, (2) a single full- stack architecture combining metadata lineage, privacy assurance, and analytical preparedness, and (3) experimental validation of significant quality and compliance improvement
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