Big Data Fundamentals: Concepts, Drivers & Techniques (Paperback) (大數據基礎：概念、驅動因素與技術)

Thomas Erl, Wajid Khattak, Paul Buhler

Big Data Fundamentals: Concepts, Drivers & Techniques (Paperback)

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商品描述

“This text should be required reading for everyone in contemporary business.”
--Peter Woodhull, CEO, Modus21

“The one book that clearly describes and links Big Data concepts to business utility.”
--Dr. Christopher Starr, PhD

“Simply, this is the best Big Data book on the market!”
--Sam Rostam, Cascadian IT Group

“...one of the most contemporary approaches I’ve seen to Big Data fundamentals...”
--Joshua M. Davis, PhD

The Definitive Plain-English Guide to Big Data for Business and Technology Professionals

Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams.

The authors begin by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, they demystify key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages.
  • Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data science
  • Understanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovation
  • Planning strategic, business-driven Big Data initiatives
  • Addressing considerations such as data management, governance, and security
  • Recognizing the 5 “V” characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and value
  • Clarifying Big Data’s relationships with OLTP, OLAP, ETL, data warehouses, and data marts
  • Working with Big Data in structured, unstructured, semi-structured, and metadata formats
  • Increasing value by integrating Big Data resources with corporate performance monitoring
  • Understanding how Big Data leverages distributed and parallel processing
  • Using NoSQL and other technologies to meet Big Data’s distinct data processing requirements
  • Leveraging statistical approaches of quantitative and qualitative analysis
  • Applying computational analysis methods, including machine learning

商品描述(中文翻譯)

「這本書應該是當代商業界每個人都應該閱讀的必讀之作。」
-- Peter Woodhull, Modus21 CEO

「這本書是唯一清楚描述並將大數據概念與商業效益聯繫起來的書籍。」
-- Dr. Christopher Starr, 博士

「簡單來說，這是市場上最好的大數據書籍！」
-- Sam Rostam, Cascadian IT Group

「...這是我見過的對大數據基礎知識最現代的方法之一...」
-- Joshua M. Davis, 博士

《大數據基礎知識》是一本為商業和技術專業人士提供的明確易懂的大數據指南。暢銷IT作家Thomas Erl及其團隊清楚地解釋了關鍵的大數據概念、理論和術語，以及基本技術和技巧。所有內容都有案例研究示例和許多簡單的圖表支持。

作者們首先解釋了大數據如何通過解決一系列以前棘手的商業問題來推動組織發展。接下來，他們揭示了關鍵分析技術和技術的神秘面紗，並展示了如何建立和整合大數據解決方案環境以提供競爭優勢。


  • 了解大數據的基本概念，以及它與以前的數據分析和數據科學的不同之處

  • 理解採用大數據的商業動機和驅動因素，從運營改善到創新

  • 規劃戰略性、以業務為導向的大數據項目

  • 解決數據管理、治理和安全等考慮因素

  • 認識大數據環境中數據集的5個「V」特徵：數量、速度、多樣性、真實性和價值

  • 澄清大數據與OLTP、OLAP、ETL、數據倉庫和數據集市的關係

  • 處理結構化、非結構化、半結構化和元數據格式的大數據

  • 通過將大數據資源與企業績效監控整合來提高價值

  • 了解大數據如何利用分散和並行處理

  • 使用NoSQL和其他技術滿足大數據的獨特數據處理需求

  • 利用定量和定性分析的統計方法

  • 應用計算分析方法，包括機器學習

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