Big data : principles and paradigms
著者
書誌事項
Big data : principles and paradigms
Morgan Kaufmann, an imprint of Elsevier, c2016
- : [pbk.]
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.
To help realize Big Data's full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.
目次
Part I: Big Data Science
Part II: Big Data Infrastructures and Platforms
Part III: Big Data Security and Policy
Part IV: Big Data Applications
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