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Titlebook: New Horizons for a Data-Driven Economy; A Roadmap for Usage José María Cavanillas,Edward Curry,Wolfgang Wahlst Book‘‘‘‘‘‘‘‘ 2016 The Edito

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發(fā)表于 2025-3-21 17:47:47 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱New Horizons for a Data-Driven Economy
副標(biāo)題A Roadmap for Usage
編輯José María Cavanillas,Edward Curry,Wolfgang Wahlst
視頻videohttp://file.papertrans.cn/666/665337/665337.mp4
概述Provides the big picture on how to exploit big data, including technological, economic, political and societal issues.Details the complete lifecycle of the big data value chain, ranging from data acqu
圖書封面Titlebook: New Horizons for a Data-Driven Economy; A Roadmap for Usage José María Cavanillas,Edward Curry,Wolfgang Wahlst Book‘‘‘‘‘‘‘‘ 2016 The Edito
描述.In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. .The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Researc
出版日期Book‘‘‘‘‘‘‘‘ 2016
關(guān)鍵詞Big Data; Data Management; Data Value; Data-Driven Economy; Information Extraction; Information Integrati
版次1
doihttps://doi.org/10.1007/978-3-319-21569-3
isbn_softcover978-3-319-79353-5
isbn_ebook978-3-319-21569-3
copyrightThe Editor(s) (if applicable) and the Author(s) 2016
The information of publication is updating

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發(fā)表于 2025-3-21 21:20:19 | 只看該作者
https://doi.org/10.1007/978-3-319-21569-3Big Data; Data Management; Data Value; Data-Driven Economy; Information Extraction; Information Integrati
板凳
發(fā)表于 2025-3-22 01:25:24 | 只看該作者
地板
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strates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Researc978-3-319-79353-5978-3-319-21569-3
6#
發(fā)表于 2025-3-22 16:14:47 | 只看該作者
Big Data Acquisitionor big data acquisition for companies. The second goal is to unveil the current approaches used for data acquisition in the different sectors. Finally, it discusses how the requirements of data acquisition are met by current approaches as well as possible future developments in the same area.
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發(fā)表于 2025-3-22 18:53:03 | 只看該作者
Big Data Curationmic models, incentive models, social aspects, and supporting standards. This analysis is grounded by literature research, interviews with domain experts, surveys, and case studies and provides an overview of the state-of-the-art, future requirements and emerging trends in the field.
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發(fā)表于 2025-3-22 22:20:41 | 只看該作者
Big Data Storageelational database systems, (2) the major technical barrier to widespread up-take of big data storage solutions are missing standards, and (3) there is a need to address open research challenges related to the scalability and performance of graph databases.
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發(fā)表于 2025-3-23 01:59:06 | 只看該作者
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發(fā)表于 2025-3-23 09:25:30 | 只看該作者
Big Data in the Public Sectore are open research questions to be addressed in order to develop such technologies so competitive and effective solutions can be built. The main developments are required in the fields of scalability of data analysis, pattern discovery, and real-time applications. Also required are improvements in
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