Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information (Paperback)

Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators.

. Learn general methods for specifying Big Data in a way that is understandable to humans and to computers.

. Avoid the pitfalls in Big Data design and analysis.

. Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources.

《大數據原則》幫助讀者避免常見的錯誤，以免危及所有大數據項目。通過強調簡單、基本的概念，本書教授讀者如何組織大量複雜的數據，以及在數據內容不斷變化時如何實現數據的永久性。書中強調了對大數據資源進行數據驗證和驗證的一般方法。當數據對象具有語義支持（即以唯一標識的數據對象類別組織）時，本書展示了熟練的分析師如何在不同的大數據資源中找到數據對象之間的關係。讀者將學習如何將其數據與其他資源的數據集成，以及如何利用從大數據資源中提取的數據用於超出數據創建者想像的目的。

學習將大數據以一種對人類和計算機都易於理解的方式進行規範的一般方法。

避免在大數據設計和分析中遇到的陷阱。

了解如何在遵守一套適用於大數據資源的取得、分發和整合的法律、法規和道德標準的情況下安全、負責地創建和使用大數據。