DC Field | Value | Language |
dc.contributor.author | DJOUAD, KAwther | - |
dc.date.accessioned | 2023-10-17T13:59:05Z | - |
dc.date.available | 2023-10-17T13:59:05Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://repository.esi-sba.dz/jspui/handle/123456789/550 | - |
dc.description | Encadrant : MAHAMMED Nadir / Co-encadranr : FAHSI Mahmoud / VELCIN Julien | en_US |
dc.description.abstract | Abstract :
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.iso | en | en_US |
dc.subject | Big Data | en_US |
dc.subject | Data Lakes | en_US |
dc.subject | NLP | en_US |
dc.subject | Information Retrieval | en_US |
dc.subject | Mongodb | en_US |
dc.subject | Dash Library | en_US |
dc.title | Development of a web interface for the analysis and search of French literary data lakes for a LIFRANUM project. | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Ingénieur
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