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About this paper
Yan Zhao, Imen Megdiche, Franck Ravat
This research introduces a comprehensive metadata model and management system specifically for the data ingestion phase of Data Lakes. The work details formalized algorithms for metadata capture and demonstrates a functional system using a graph database, enabling enhanced data discoverability and preventing Data Lakes from becoming unmanageable.
Key insights
- Comprehensive metadata capture from the ingestion phase is critical to prevent Data Lakes from becoming "Data Swamps," ensuring data Findability, Accessibility, Interoperability, and Reusability (FAIR).
- A formalized, holistic metadata model that integrates information about external sources, ingestion processes, and ingested data (including veracity and security) is essential for effective Data Lake governance.
- Graph databases (e.g., Neo4j) are well-suited for storing and managing complex, interconnected metadata due to their flexibility and ability to represent relationships efficiently.
Summary by alphaXiv.
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