Big Data: Principles and Paradigms
暫譯: 大數據:原則與範式
Rajkumar Buyya (Editor), Rodrigo N. Calheiros (Editor), Amir Vahid Dastjerdi (Editor)
- 出版商: Morgan Kaufmann
- 出版日期: 2016-06-03
- 售價: $3,070
- 貴賓價: 9.5 折 $2,917
- 語言: 英文
- 頁數: 494
- 裝訂: Paperback
- ISBN: 0128053941
- ISBN-13: 9780128053942
-
相關分類:
大數據 Big-data
海外代購書籍(需單獨結帳)
買這商品的人也買了...
-
$820$648 -
$590$502 -
$403營銷數據科學:用 R 和 Python 進行預測分析的建模技術
-
$500$395 -
$520$406 -
$301Microsoft Azure 機器學習和預測分析
-
$505微軟 Azure 實戰參考
-
$834$792
商品描述
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.
- Covers computational platforms supporting Big Data applications
- Addresses key principles underlying Big Data computing
- Examines key developments supporting next generation Big Data platforms
- Explores the challenges in Big Data computing and ways to overcome them
- Contains expert contributors from both academia and industry
商品描述(中文翻譯)
《大數據:原則與範式》捕捉了大數據在架構方面、技術及應用的最前沿研究。本書識別了未來可能的方向和技術,這些技術能夠促進對眾多科學、商業和消費應用的深入理解。
為了幫助實現大數據的全部潛力,本書針對眾多挑戰進行探討,提供了應對這些挑戰的概念性和技術性解決方案。這些挑戰包括生命週期數據管理、大規模存儲、靈活的處理基礎設施、數據建模、可擴展的機器學習、數據分析算法、抽樣技術以及隱私和倫理問題。
- 涵蓋支持大數據應用的計算平台
- 闡述大數據計算的關鍵原則
- 檢視支持下一代大數據平台的關鍵發展
- 探索大數據計算中的挑戰及其克服方法
- 包含來自學術界和業界的專家貢獻者