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Enabling insights and analytics with data streaming architectures and pipelines using Kafka and Hadoop

"In a large global health services company, streaming data for processing and sharing comes with its own challenges. Data science and analytics platforms need data fast, from relevant sources, to act on this data quickly and share the insights with consumers with the same speed and urgency. Joi...

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Bibliographic Details
Main Author: Quraishi Mohammad
Format: eBook
Language:English
Published: [Place of publication not identified] O'Reilly Media 2019
Subjects:
Apache Hadoop / Fast / (ocolc)fst01911570
Flux De Données (informatique)
En Continu (télécommunications)
Apache Kafka (electronic Resource)
Streaming Technology (telecommunications) / Fast / (ocolc)fst01134637
Streaming Technology (telecommunications) / Http://id.loc.gov/authorities/subjects/sh99000996
Data Flow Computing / Http://id.loc.gov/authorities/subjects/sh91004989
Data Flow Computing / Fast / (ocolc)fst00887940
Apache Hadoop / Http://id.loc.gov/authorities/names/n2013024279
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:"In a large global health services company, streaming data for processing and sharing comes with its own challenges. Data science and analytics platforms need data fast, from relevant sources, to act on this data quickly and share the insights with consumers with the same speed and urgency. Join Mohammad Quraishi (Cigna) to learn why streaming data architectures are a necessity--Kafka and Hadoop are key. Mohammad outlines architectures centered around the Hadoop Platform and Kafka that were implemented to support a variety of integration and analytics requirements. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco."--Resource description page
Item Description:Title from resource description page (Safari, viewed January 31, 2020)
Physical Description:1 streaming video file (40 min., 17 sec.)

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