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Sinopsis
Big data analytics (BDA) is important to reduce healthcare costs. However, in many hospital systems, new technologies that influence patient data require extensive technical and rigorous usability testing before implementation into production. Therefore, to implement, an existing High Performance Computing (HPC) Linux node clusters were utilized externally, and simulation of patient data benchmarked and cross-referenced with current metadata profiles in operational hospital systems at the Vancouver Island Health Authority (VIHA), Victoria, Canada. Over the tested platform, the data were generated, indexed and stored over a Hadoop Distributed File System (HDFS) to noSQL database (HBase) that represented three billion patient records. Hadoop/MapReduce framework formed the BDA platform with HBase (NoSQL database) using hospital-specific metadata and file ingestion. Queries showed high performance with a variety of Apache tools in Hadoop’s ecosystem. BDA platform of HBase distributed by Hadoop successfully under high performance at large volumes and the entire data archive. Importance on representation of health informatics using technologies for big data in healthcare is discussed.
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I am a health information technologist and platform specialist in healthcare. My current research is big data technologies and middleware application at Vancouver Island Health Authority, Canada. Five university degrees, collaboration at University of Victoria, professorship at University of Tokyo and PhD from Swedish University of Agric Sciences.
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Healthcare Big Data Analytics Platform with Hadoop/MapReduce Framework
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LAP Lambert Academic Publishing Sep 2017, 2017
ISBN 10: 3330335114
ISBN 13: 9783330335110
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Big data analytics (BDA) is important to reduce healthcare costs. However, in many hospital systems, new technologies that influence patient data require extensive technical and rigorous usability testing before implementation into production. Therefore, to implement, an existing High Performance Computing (HPC) Linux node clusters were utilized externally, and simulation of patient data benchmarked and cross-referenced with current metadata profiles in operational hospital systems at the Vancouver Island Health Authority (VIHA), Victoria, Canada. Over the tested platform, the data were generated, indexed and stored over a Hadoop Distributed File System (HDFS) to noSQL database (HBase) that represented three billion patient records. Hadoop/MapReduce framework formed the BDA platform with HBase (NoSQL database) using hospital-specific metadata and file ingestion. Queries showed high performance with a variety of Apache tools in Hadoop's ecosystem. BDA platform of HBase distributed by Hadoop successfully under high performance at large volumes and the entire data archive. Importance on representation of health informatics using technologies for big data in healthcare is discussed. 136 pp. Englisch. Nº de ref. del artículo: 9783330335110
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Healthcare Big Data Analytics Platform with Hadoop/MapReduce Framework
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330335114
ISBN 13: 9783330335110
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chrimes DillonI am a health information technologist and platform specialist in healthcare. My current research is big data technologies and middleware application at Vancouver Island Health Authority, Canada. Five university degrees. Nº de ref. del artículo: 167666852
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Healthcare Big Data Analytics Platform with Hadoop/MapReduce Framework
Publicado por
LAP Lambert Academic Publishing Sep 2017, 2017
ISBN 10: 3330335114
ISBN 13: 9783330335110
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Big data analytics (BDA) is important to reduce healthcare costs. However, in many hospital systems, new technologies that influence patient data require extensive technical and rigorous usability testing before implementation into production. Therefore, to implement, an existing High Performance Computing (HPC) Linux node clusters were utilized externally, and simulation of patient data benchmarked and cross-referenced with current metadata profiles in operational hospital systems at the Vancouver Island Health Authority (VIHA), Victoria, Canada. Over the tested platform, the data were generated, indexed and stored over a Hadoop Distributed File System (HDFS) to noSQL database (HBase) that represented three billion patient records. Hadoop/MapReduce framework formed the BDA platform with HBase (NoSQL database) using hospital-specific metadata and file ingestion. Queries showed high performance with a variety of Apache tools in Hadoop¿s ecosystem. BDA platform of HBase distributed by Hadoop successfully under high performance at large volumes and the entire data archive. Importance on representation of health informatics using technologies for big data in healthcare is discussed.Books on Demand GmbH, Überseering 33, 22297 Hamburg 136 pp. Englisch. Nº de ref. del artículo: 9783330335110
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Healthcare Big Data Analytics Platform with Hadoop/MapReduce Framework
Publicado por
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330335114
ISBN 13: 9783330335110
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Librería: Revaluation Books, Exeter, Reino Unido
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Paperback. Condición: Brand New. 136 pages. 8.66x5.91x0.31 inches. In Stock. Nº de ref. del artículo: 3330335114
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Healthcare Big Data Analytics Platform with Hadoop/MapReduce Framework
Publicado por
LAP Lambert Academic Publishing, 2017
ISBN 10: 3330335114
ISBN 13: 9783330335110
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Big data analytics (BDA) is important to reduce healthcare costs. However, in many hospital systems, new technologies that influence patient data require extensive technical and rigorous usability testing before implementation into production. Therefore, to implement, an existing High Performance Computing (HPC) Linux node clusters were utilized externally, and simulation of patient data benchmarked and cross-referenced with current metadata profiles in operational hospital systems at the Vancouver Island Health Authority (VIHA), Victoria, Canada. Over the tested platform, the data were generated, indexed and stored over a Hadoop Distributed File System (HDFS) to noSQL database (HBase) that represented three billion patient records. Hadoop/MapReduce framework formed the BDA platform with HBase (NoSQL database) using hospital-specific metadata and file ingestion. Queries showed high performance with a variety of Apache tools in Hadoop's ecosystem. BDA platform of HBase distributed by Hadoop successfully under high performance at large volumes and the entire data archive. Importance on representation of health informatics using technologies for big data in healthcare is discussed. Nº de ref. del artículo: 9783330335110
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