A generic metadata management model for heterogeneous sources in a data warehouse
| Autor: | Lamya Oukhouya, Hiba Asri, Brahim Er-raha, Anass El Haddadi |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Database
Exploit Computer science business.industry Big data Conceptual model (computer science) Web Ontology Language Metadata modeling computer.software_genre Data warehouse Environmental sciences ComputingMethodologies_PATTERNRECOGNITION Metadata management Business intelligence GE1-350 business computer computer.programming_language |
| Zdroj: | E3S Web of Conferences, Vol 297, p 01069 (2021) |
| ISSN: | 2267-1242 |
| Popis: | For more than 30 decades, data warehouses have been considered the only business intelligence storage system for enterprises. However, with the advent of big data, they have been modernized to support the variety and dynamics of data by adopting the data lake as a centralized data source for heterogeneous sources. Indeed, the data lake is characterized by its flexibility and performance when storing and analyzing data. However, the absence of schema on the data during ingestion increases the risk of the transformation of the data lake into a data swamp, so the use of metadata management is essential to exploit the data lake. In this paper, we will present a conceptual metadata management model for the data lake. Our solution will be based on a functional architecture of the data lake as well as on a set of features allowing the genericity of the metadata model. Furthermore, we will present a set of transformation rules, allowing us to translate our conceptual model into an owl ontology. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|