Abstract
Over the last decade, the data lake concept has emerged as an alternative to data warehouses for data storage and analysis. Data lakes adopt a schema-on-read approach to provide a flexible and extendable decision support system. In absence of a fixed schema, data querying and exploration depend on a metadata system. However, existing works on metadata management in data lakes mainly focus on structured and semi-structured data, with little research on unstructured data. Thence, we propose in this thesis a methodological approach to enable textual data analyses from data lakes through an efficient metadata system.
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