國立虎尾科技大學 |

Designing big data platforms = how to use, deploy, and maintain big data systems /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Designing big data platforms/ Yusuf Aytas.
其他題名:	how to use, deploy, and maintain big data systems /
作者:	Aytas, Yusuf.
出版者:	Hoboken, NJ :Wiley, : 2021.,
面頁冊數:	1 online resource (273 p.)
標題:	Database management. -
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119690962
ISBN:	9781119690962

Designing big data platforms = how to use, deploy, and maintain big data systems /
Aytas, Yusuf.

Designing big data platformshow to use, deploy, and maintain big data systems /[electronic resource] :Yusuf Aytas. - Hoboken, NJ :Wiley,2021. - 1 online resource (273 p.)

Includes bibliographical references and index.

Front Matter -- An Introduction: What's a Modern Big Data Platform -- A Bird's Eye View on Big Data -- A Minimal Data Processing and Management System -- Big Data Storage -- Offline Big Data Processing -- Stream Big Data Processing -- Data Analytics -- Data Science -- Data Discovery -- Data Security -- Putting All Together -- An Ideal Platform -- Appendix A: Further Systems and Patterns -- Appendix B: Recipes.

An array of tools are currently available for managing and processing data-some are ready-to-go solutions that can be immediately deployed, while others require complex and time-intensive setups. With such a vast range of options, choosing the right tool to build a solution can be complicated, as can determining which tools work well with each other. Designing Big Data Platforms provides clear and authoritative guidance on the critical decisions necessary for successfully deploying, operating, and maintaining Big Data systems. This highly practical guide helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security.

ISBN: 9781119690962

Standard No.: 10.1002/9781119690962doiSubjects--Topical Terms:

557799
Database management.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Designing big data platforms = how to use, deploy, and maintain big data systems /
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245 1 0 $a Designing big data platforms $h [electronic resource] : $b how to use, deploy, and maintain big data systems / $c Yusuf Aytas.
260 $a Hoboken, NJ : $b Wiley, $c 2021.
300 $a 1 online resource (273 p.)
504 $a Includes bibliographical references and index.
505 0 $a Front Matter -- An Introduction: What's a Modern Big Data Platform -- A Bird's Eye View on Big Data -- A Minimal Data Processing and Management System -- Big Data Storage -- Offline Big Data Processing -- Stream Big Data Processing -- Data Analytics -- Data Science -- Data Discovery -- Data Security -- Putting All Together -- An Ideal Platform -- Appendix A: Further Systems and Patterns -- Appendix B: Recipes.
520 $a An array of tools are currently available for managing and processing data-some are ready-to-go solutions that can be immediately deployed, while others require complex and time-intensive setups. With such a vast range of options, choosing the right tool to build a solution can be complicated, as can determining which tools work well with each other. Designing Big Data Platforms provides clear and authoritative guidance on the critical decisions necessary for successfully deploying, operating, and maintaining Big Data systems. This highly practical guide helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security.
588 $a Description based on print version record.
650 0 $a Database management. $3 557799
650 0 $a Big data. $3 981821
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119690962