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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
