Automated Column-Level Data Lineage and Audit Trails for GDPR Compliance in Marketing Technology Platforms
Keywords:
GDPR compliance, Marketing Technology platforms, column-level data lineage, audit trails, data governance, automated tracking, data transparency, regulatory accountability.Abstract
This study examined the development and evaluation of automated column-level data lineage and audit-trail mechanisms designed to enhance GDPR compliance within Marketing Technology (MarTech) platforms. With the increasing complexity of marketing data pipelines, tracking the movement, transformation, and access of highly granular user data has become critical for ensuring regulatory compliance. A design-science methodology was employed to develop and evaluate a prototype system that automatically captured column-level lineage across ingestion, transformation, and activation processes and generated immutable audit records for all data operations. The system was evaluated using synthetic datasets and qualitative assessments from data governance professionals. Results demonstrated that 94% of columns were accurately traced, 96% of events were fully recorded, and experts rated the system highly for transparency, accountability, and support for regulatory reporting. The findings indicated that automated lineage and audit-trail frameworks significantly improve traceability, reduce compliance gaps, and strengthen organisational readiness for GDPR audits. Minor limitations were identified in handling complex transformations and concurrent operations, highlighting opportunities for further refinement. Overall, the study provides evidence that automated column-level lineage and audit-trail mechanisms can serve as a reliable approach for compliance-driven data governance in MarTech environments.
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