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"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"--Provided by publisher.

Information systems --- big data --- datawarehousing

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This book offers data-based insights into the problems of translation education and their causes in the context of localization and globalization in the era of big data. By examining language services around the globe, illustrating applications of big-data technology and their future development, and describing crowdsourcing and online collaborative translations, speech-to-speech translation and cloud-based translation, it makes readers aware of the important changes taking place in the professional translation market and consequently recognize the insufficiency of translation education and the need for it to be restructured accordingly. Furthermore, the book includes data-based analyses of translation education problems, such as teaching philosophy, curriculum design and faculty development of both undergraduate and postgraduate education in China. More importantly, it proposes solutions that have already been successful in experiments in a number of universities in China for other institutions of higher education to imitate in restructuring translation education. The discussion is of interest for current and future translation policy makers, translation educators, translators and learners.

Mathematical linguistics --- Linguistics --- big data --- China

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Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.

Computational intelligence. --- Cloud computing. --- Big data.

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Big data --- Social aspects --- Social aspects. --- social science --- big data --- society --- computing

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Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging Big Data and analytics.Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts strategic directions and practical analytical solutions on how to create value from existing and new big data.By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research and customer relationship management.

Information systems --- Marketing --- Big data --- data acquisition --- marketing