Big data application architecture Q & A a problem-solution approach
Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the...
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Format: | Elektronisch E-Book |
Sprache: | English |
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[New York]
Apress
2013
[New York] Distributed by Springer Science+Business Media New York 2013 |
Schriftenreihe: | The expert's voice in big data
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500 | |a Includes bibliographical references and index. - Online resource; title from title page (Safari, viewed February 10, 2014) | ||
520 | |a Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits. Big Data Application Architecture Pattern Recipes answers one of the most critical questions of this time 'how do you select the best end-to-end architecture to solve your big data problem?'. The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution, trying to extract insight from huge volumes of data in real-time and across multiple relational and non-relational data types for clients from industries like retail, telecommunication, banking, and insurance. The patterns in this book provide the strong architectural foundation required to launch your next big data application. The architectures for realizing these opportunities are based on relatively less expensive and heterogeneous infrastructures compared to the traditional monolithic and hugely expensive options that exist currently. This book describes and evaluates the benefits of heterogeneity which brings with it multiple options of solving the same problem, evaluation of trade-offs and validation of 'fitness-for-purpose' of the solution. | ||
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Datensatz im Suchindex
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adam_text | |
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author | Sawant, Nitin |
author2 | Shah, Himanshu |
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discipline | Informatik |
format | Electronic eBook |
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illustrated | Illustrated |
indexdate | 2024-12-18T08:47:54Z |
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language | English |
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publishDate | 2013 |
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publisher | Apress Distributed by Springer Science+Business Media New York |
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series2 | The expert's voice in big data |
spelling | Sawant, Nitin VerfasserIn aut Big data application architecture Q & A a problem-solution approach Nitin Sawant, Himanshu Shah [New York] Apress 2013 [New York] Distributed by Springer Science+Business Media New York 2013 1 online resource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The expert's voice in big data Includes bibliographical references and index. - Online resource; title from title page (Safari, viewed February 10, 2014) Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits. Big Data Application Architecture Pattern Recipes answers one of the most critical questions of this time 'how do you select the best end-to-end architecture to solve your big data problem?'. The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution, trying to extract insight from huge volumes of data in real-time and across multiple relational and non-relational data types for clients from industries like retail, telecommunication, banking, and insurance. The patterns in this book provide the strong architectural foundation required to launch your next big data application. The architectures for realizing these opportunities are based on relatively less expensive and heterogeneous infrastructures compared to the traditional monolithic and hugely expensive options that exist currently. This book describes and evaluates the benefits of heterogeneity which brings with it multiple options of solving the same problem, evaluation of trade-offs and validation of 'fitness-for-purpose' of the solution. English. Big data Software architecture Data mining Data Mining Données volumineuses Architecture logicielle Exploration de données (Informatique) COMPUTERS ; Computer Literacy COMPUTERS ; Computer Science COMPUTERS ; Data Processing COMPUTERS ; Hardware ; General COMPUTERS ; Information Technology COMPUTERS ; Machine Theory COMPUTERS ; Reference Shah, Himanshu MitwirkendeR ctb 9781430262923 Erscheint auch als Druck-Ausgabe 9781430262923 TUM01 ZDB-30-ORH TUM_PDA_ORH https://learning.oreilly.com/library/view/-/9781430262923/?ar X:ORHE Aggregator lizenzpflichtig Volltext |
spellingShingle | Sawant, Nitin Big data application architecture Q & A a problem-solution approach Big data Software architecture Data mining Data Mining Données volumineuses Architecture logicielle Exploration de données (Informatique) COMPUTERS ; Computer Literacy COMPUTERS ; Computer Science COMPUTERS ; Data Processing COMPUTERS ; Hardware ; General COMPUTERS ; Information Technology COMPUTERS ; Machine Theory COMPUTERS ; Reference |
title | Big data application architecture Q & A a problem-solution approach |
title_auth | Big data application architecture Q & A a problem-solution approach |
title_exact_search | Big data application architecture Q & A a problem-solution approach |
title_full | Big data application architecture Q & A a problem-solution approach Nitin Sawant, Himanshu Shah |
title_fullStr | Big data application architecture Q & A a problem-solution approach Nitin Sawant, Himanshu Shah |
title_full_unstemmed | Big data application architecture Q & A a problem-solution approach Nitin Sawant, Himanshu Shah |
title_short | Big data application architecture Q & A |
title_sort | big data application architecture q a a problem solution approach |
title_sub | a problem-solution approach |
topic | Big data Software architecture Data mining Data Mining Données volumineuses Architecture logicielle Exploration de données (Informatique) COMPUTERS ; Computer Literacy COMPUTERS ; Computer Science COMPUTERS ; Data Processing COMPUTERS ; Hardware ; General COMPUTERS ; Information Technology COMPUTERS ; Machine Theory COMPUTERS ; Reference |
topic_facet | Big data Software architecture Data mining Data Mining Données volumineuses Architecture logicielle Exploration de données (Informatique) COMPUTERS ; Computer Literacy COMPUTERS ; Computer Science COMPUTERS ; Data Processing COMPUTERS ; Hardware ; General COMPUTERS ; Information Technology COMPUTERS ; Machine Theory COMPUTERS ; Reference |
url | https://learning.oreilly.com/library/view/-/9781430262923/?ar |
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