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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/550
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dc.contributor.authorDJOUAD, KAwther-
dc.date.accessioned2023-10-17T13:59:05Z-
dc.date.available2023-10-17T13:59:05Z-
dc.date.issued2023-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/550-
dc.descriptionEncadrant : MAHAMMED Nadir / Co-encadranr : FAHSI Mahmoud / VELCIN Julienen_US
dc.description.abstractAbstract : In the age of information abundance, data lakes have emerged as a foundational element in the management of big data. These centralized repositories offer organizations the ability to efficiently store and analyze vast and diverse datasets from a multitude of sources, including social media, IoT devices, and enterprise systems. Data lakes provide a scalable and cost-effective solution, allowing data to be ingested in real-time or batches, stored in distributed file systems or cloud platforms, and processed using powerful frameworks like Apache Hadoop and Apache Spark. Effective data lake management entails meticulous data organization, metadata management, and data governance to ensure data accuracy, discoverability, and usability, empowering businesses to extract valuable insights and make data-driven decisions in an increasingly data-driven world.en_US
dc.language.isoenen_US
dc.subjectBig Dataen_US
dc.subjectData Lakesen_US
dc.subjectNLPen_US
dc.subjectInformation Retrievalen_US
dc.subjectMongodben_US
dc.subjectDash Libraryen_US
dc.titleDevelopment of a web interface for the analysis and search of French literary data lakes for a LIFRANUM project.en_US
dc.typeThesisen_US
Appears in Collections:Ingénieur

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