Pro Hadoop Data Analytics

Kerry Koitzsch

ISBN 10: 1484219090 / ISBN 13: 9781484219096

Editore: Apress, Apress Dez 2016, 2016

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Neuware -Learn advanced analytical techniques and leverage existing tool kits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems that go beyond the basics of classification, clustering, and recommendation.Pro Hadoop Data Analytics emphasizes best practices to ensure coherent, efficient development. A complete example system will be developed using standard third-party components that consist of the tool kits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.The book also highlights the importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. You'll discover the importance of mix-and-match or hybrid systems, using different analytical components in one application. This hybrid approach will be prominent in the examples.What You'll LearnAPress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 324 pp. Englisch. Codice articolo 9781484219096

Dati bibliografici

Titolo: Pro Hadoop Data Analytics

Casa editrice: Apress, Apress Dez 2016

Data di pubblicazione: 2016

Legatura: Taschenbuch

Condizione: Neu

Descrizione articolo

Riassunto:

Learn advanced analytical techniques and leverage existing tool kits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems that go beyond the basics of classification, clustering, and recommendation.

Pro Hadoop Data Analytics emphasizes best practices to ensure coherent, efficient development. A complete example system will be developed using standard third-party components that consist of the tool kits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.

The book also highlights the importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. You'll discover the importance of mix-and-match or hybrid systems, using different analytical components in one application. This hybrid approach will be prominent in the examples.

What You'll Learn 

• Build big data analytic systems with the Hadoop ecosystem
• Use libraries, tool kits, and algorithms to make development easier and more effective
• Apply metrics to measure performance and efficiency of components and systems
• Connect to standard relational databases, noSQL data sources, and more
• Follow case studies with example components to create your own systems

Who This Book Is For

Software engineers, architects, and data scientists with an interest in the design and implementation of big data analytical systems using Hadoop, the Hadoop ecosystem, and other associated technologies.

Informazioni sull?autore:

Kerry Koitzsch is a software engineer and interested in the early history of science, particularly chemistry. He frequently publishes papers and attends conferences on scientific and historical topics, including early chemistry and alchemy, and sociology of science. He has presented many lectures, talks, and demonstrations on a variety of subjects for the United States Army, the Society for Utopian Studies, American Association for Artificial Intelligence (AAAI), Association for Studies in Esotericism (ASE), and others. He has also published several papers and written two historical books.

Kerry was educated at Interlochen Arts Academy, MIT, and the San Francisco Conservatory of Music. He served in the United States Army and United States Army Reserve, and is the recipient of the United States Army Achievement Medal.  He has been a software engineer specializing in computer vision, machine learning, and database technologies for 30 years, and currently lives and works in Sunnyvale, California.