Data Warehouse Metadata Repository Design

Abstract

Data warehouse metadata repository design is important because enterprise warehouses require clear documentation of data sources, structures, transformations, ownership, lineage, and reporting usage. A metadata repository stores technical, business, and operational metadata that helps users understand how data is extracted, transformed, loaded, stored, and consumed across analytical systems. Existing literature highlights data lineage, source-to-target mapping, data definitions, ETL metadata, schema documentation, business glossaries, audit details, and governance controls as major components of metadata repository design. However, many organizations still face challenges such as inconsistent data definitions, undocumented transformation rules, unclear data ownership, weak lineage tracking, duplicated metadata, and difficulty tracing report-level data back to source systems. This research is important because poor metadata management can reduce data trust, slow troubleshooting, weaken compliance reporting, and affect decision-making accuracy. This article discusses data warehouse metadata repository design, focusing on metadata classification, repository structure, lineage capture, ETL documentation, business term management, access control, and update governance. The study concludes that an effective metadata repository improves warehouse transparency, strengthens data governance, supports faster impact analysis, and enhances the reliability of enterprise analytics.