Fast data with the KISSS stack /

"Bas Geerdink (Aizonic) presents an architecture for streaming analytics solutions that covers many use cases that follow this pattern: actionable insights, fraud detection, log parsing, traffic analysis, factory data, the IoT, and others. He explores a few architecture challenges that arise wh...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media, 2019.
Temas:
O'Reilly Strata Data Conference > (2019 : > New York, N.Y.)
Real-time data processing.
Electronic data processing > Distributed processing.
Artificial intelligence.
Machine learning.
Artificial Intelligence
Temps réel (Informatique)
Traitement réparti.
Intelligence artificielle.
Apprentissage automatique.
artificial intelligence.
Artificial intelligence
Electronic data processing > Distributed processing
Machine learning
Real-time data processing
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:"Bas Geerdink (Aizonic) presents an architecture for streaming analytics solutions that covers many use cases that follow this pattern: actionable insights, fraud detection, log parsing, traffic analysis, factory data, the IoT, and others. He explores a few architecture challenges that arise when dealing with streaming data, such as latency issues, event time versus server time, and exactly once processing. The solution is open source and available on GitHub: build on the KISSS stack. This session is from the 2019 O'Reilly Strata Conference in New York, NY."--Resource description page
Notas:Title from title screen (viewed July 23, 2020).
Descripción Física:1 online resource (1 streaming video file (39 min., 33 sec.))

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