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  • 1
    UID:
    b3kat_BV043546431
    Format: 1 Online-Ressource (XX, 303 p. 34 illus)
    ISBN: 9783319215693
    Additional Edition: Erscheint auch als Druckausgabe ISBN 978-3-319-21568-6
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    RVK:
    Keywords: Informatik ; Information Retrieval ; Betriebsführung ; Informationsspeicherung ; Aufsatzsammlung ; Electronic books
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Full-text  ((OIS Credentials Required))
    Author information: Wahlster, Wolfgang 1953-
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    almahu_BV043519360
    Format: xx, 303 Seiten : , Illustrationen, Diagramme.
    ISBN: 978-3-319-21568-6
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    RVK:
    Keywords: Informatik ; Information Retrieval ; Betriebsführung ; Informationsspeicherung ; Aufsatzsammlung
    Author information: Wahlster, Wolfgang 1953-
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    edoccha_9958115365502883
    Format: 1 online resource (XX, 303 pages) : , 34 illustrations; digital file(s).
    Edition: 1st ed. 2016.
    ISBN: 3-319-21569-8
    Content: 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 Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.                                                    .
    Note: Bibliographic Level Mode of Issuance: Monograph , Part I: The Big Data Opportunity -- The Big Data Value Opportunity -- Introduction to the BIG Project -- Part II: The Big Data Value Chain: Enabling and Value Creating Technologies -- The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches -- Big Data Acquisition -- Big Data Analysis -- Big Data Curation -- Big Data Storage -- Big Data Usage -- Part III: Usage and Exploitation of Big Data -- Big Data Driven Innovation in Industrial Sectors -- Big Data in the Health Sector -- Big Data in the Public Sector -- Big Data in the Finance and Insurance Sectors -- Big Data in the Energy and Transport Sectors -- Big Data in the Media and Entertainment Sectors -- Part IV: A Roadmap for Big Data Research -- Cross-Sectorial Requirements Analysis for Big Data Research -- New Horizons for a Data-Driven Economy: Roadmaps and Action Plans for Technology, Businesses, Policy, and Society.                        . , Also available in print form. , English
    Additional Edition: Print version: ISBN 9783319215686
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    edocfu_9958115365502883
    Format: 1 online resource (XX, 303 pages) : , 34 illustrations; digital file(s).
    Edition: 1st ed. 2016.
    ISBN: 3-319-21569-8
    Content: 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 Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.                                                    .
    Note: Bibliographic Level Mode of Issuance: Monograph , Part I: The Big Data Opportunity -- The Big Data Value Opportunity -- Introduction to the BIG Project -- Part II: The Big Data Value Chain: Enabling and Value Creating Technologies -- The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches -- Big Data Acquisition -- Big Data Analysis -- Big Data Curation -- Big Data Storage -- Big Data Usage -- Part III: Usage and Exploitation of Big Data -- Big Data Driven Innovation in Industrial Sectors -- Big Data in the Health Sector -- Big Data in the Public Sector -- Big Data in the Finance and Insurance Sectors -- Big Data in the Energy and Transport Sectors -- Big Data in the Media and Entertainment Sectors -- Part IV: A Roadmap for Big Data Research -- Cross-Sectorial Requirements Analysis for Big Data Research -- New Horizons for a Data-Driven Economy: Roadmaps and Action Plans for Technology, Businesses, Policy, and Society.                        . , Also available in print form. , English
    Additional Edition: Print version: ISBN 9783319215686
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    UID:
    almahu_9947382379502882
    Format: 1 online resource (XX, 303 pages) : , 34 illustrations; digital file(s).
    Edition: 1st ed. 2016.
    ISBN: 3-319-21569-8
    Content: 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 Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.                                                    .
    Note: Bibliographic Level Mode of Issuance: Monograph , Part I: The Big Data Opportunity -- The Big Data Value Opportunity -- Introduction to the BIG Project -- Part II: The Big Data Value Chain: Enabling and Value Creating Technologies -- The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches -- Big Data Acquisition -- Big Data Analysis -- Big Data Curation -- Big Data Storage -- Big Data Usage -- Part III: Usage and Exploitation of Big Data -- Big Data Driven Innovation in Industrial Sectors -- Big Data in the Health Sector -- Big Data in the Public Sector -- Big Data in the Finance and Insurance Sectors -- Big Data in the Energy and Transport Sectors -- Big Data in the Media and Entertainment Sectors -- Part IV: A Roadmap for Big Data Research -- Cross-Sectorial Requirements Analysis for Big Data Research -- New Horizons for a Data-Driven Economy: Roadmaps and Action Plans for Technology, Businesses, Policy, and Society.                        . , Also available in print form. , English
    Additional Edition: Print version: ISBN 9783319215686
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    UID:
    kobvindex_INT0003028
    Format: 1 electronic resource (xx, 303 pages) : , illustrations.
    ISBN: 9783319215686 , 331921568X , 9783319793535 , 3319793535 , 9783319215693 , 3319215698
    Content: MACHINE-GENERATED SUMMARY NOTE: "First of all, this book is not just another approach made by a single player looking down from a corner of the world. It is the compendium of more than 2 years of work performed by a set of major European research centers and industries. It is the compilation and processed synthesis of what we all have done, prepared, foreseen, and anticipated in many aspects of this challenging technological context that is becoming the major axis of the new digitally transformed business environment. [...] The book is divided into four parts: Part I "The Big Data Opportunity" explores the value potential of big data with a particular focus on the European context. [...] 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. [...] 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 Research" identifies and prioritizes the cross-sectorial requirements for big data research and outlines the most urgent and challenging technological, economic, political, and societal issues for big data in Europe."
    Content: MACHINE-GENERATED SUMMARY NOTE: "Data has become a factor just as important to production as labor, capital, and land. For the new value creators in today's technology start-ups, little capital and office space is required. Both can be almost free when a firm is growing 1 % per day, on any metric. But without talent, and without the right kind of data, such a takeoff is highly improbable. We see the same forces at play in SAP's Innovation Center Network. Attracting the right talent was critical to establish the first Innovation Center in Potsdam. And having large, real-world datasets from customers and co-innovation partners is critical to many of our innovations. To make a difference in cancer treatment and research with our Medical Research Insights app, we critically depended on datadriven collaboration with the National Center for Tumor Diseases. The same holds for incubating SAP's new sports line of business by co-innovating with the German national soccer team based on real-time sensor feeds from their players. And it holds true for SAP's many initiatives in the Internet of Things, like the predictive maintenance apps with John Deere and Kaeser. The Big Data Value Association (BDVA) is poised to make a difference both for data availability and for talent. By bringing together businesses with leading researchers, software and hardware partners, and enabling co-innovation around large, real-world datasets, BDVA can help lower the data barrier. And helping educate the next generation of thought leaders, especially in data science, computer science, and related fields, BDVA can help increase the supply of talent. Both are critical so Europe can begin to lead, not follow, in creating value from big data. By clearly defining the opportunity in big data, by examining the big data value chain, and by deep-diving into industry sector applications, this book charts a way forward to new value creation and new opportunities from big data. Decision makers, policy advisors, researchers, and practitioners on all levels can benefit from this."
    Content: MACHINE-GENERATED SUMMARY NOTE: "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 Research" identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment."
    Note: EDITORIAL NOTE: hardback edition published 2016, paperback edition published 2018. , MACHINE-GENERATED CONTENTS NOTE: Preface -- Part I The Big Data Opportunity -- 1 The Big Data Value Opportunity 3 / José María Cavanillas, Edward Curry, and Wolfgang Wahlster -- 2 The BIG Project 13 / Edward Curry, Tilman Becker, Ricard Munné, Nuria De Lama, and Sonja Zillner -- Part II The Big Data Value Chain: Enabling and Value Creating Technologies -- 3 The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches 29 / Edward Curry -- 4 Big Data Acquisition 39 / Klaus Lyko, Marcus Nitzschke, and Axel-Cyrille Ngonga Ngomo -- 5 Big Data Analysis 63 / John Domingue, Nelia Lasierra, Anna Fensel, Tim van Kasteren, Martin Strohbach, and Andreas Thalhammer -- 6 Big Data Curation 87 / Andre F́reitas and Edward Curry -- 7 Big Data Storage 119 / Martin Strohbach, J€org Daubert, Herman Ravkin, and Mario Lischka -- 8 Big Data Usage 143 / Tilman Becker -- Part III Usage and Exploitation of Big Data -- 9 Big Data-Driven Innovation in Industrial Sectors 169 / Sonja Zillner, Tilman Becker, Ricard Munné, Kazim Hussain, Sebnem Rusitschka, Helen Lippell, Edward Curry, and Adegboyega Ojo -- 10 Big Data in the Health Sector 179 / Sonja Zillner and Sabrina Neururer -- 11 Big Data in the Public Sector 195 / Ricard Munné -- 12 Big Data in the Finance and Insurance Sectors 209 / Kazim Hussain and Elsa Prieto -- 13 Big Data in the Energy and Transport Sectors 225 / Sebnem Rusitschka and Edward Curry -- 14 Big Data in the Media and Entertainment Sectors 245 / Helen Lippell -- Part IV A Roadmap for Big Data Research -- 15 Cross-sectorial Requirements Analysis for Big Data Research 263 / Tilman Becker, Edward Curry, Anja Jentzsch, and Walter Palmetshofer -- 16 New Horizons for a Data-Driven Economy: Roadmaps and Action Plans for Technology, Businesses, Policy, and Society 277 / Tilman Becker, Edward Curry, Anja Jentzsch, and Walter Palmetshofer -- Index 293.
    Language: English
    Keywords: Edited volumes ; Handbooks and manuals
    URL: FULL
    Library Location Call Number Volume/Issue/Year Availability
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  • 7
    UID:
    gbv_460327178
    Note: In: Revista de plásticos modernos. - Madrid , Año 34(1983), Nr. 328, S. 383-395, mit Tab
    In: year:1983
    Language: Spanish
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  • 8
    UID:
    almahu_9949301199402882
    Format: 1 online resource (312 pages)
    ISBN: 9783319215693
    Note: Intro -- Foreword -- Foreword -- Preface -- Book Acknowledgements -- Project Acknowledgements -- Contents -- List of Contributors -- Part I: The Big Data Opportunity -- Chapter 1: The Big Data Value Opportunity -- 1.1 Introduction -- 1.2 Harnessing Big Data -- 1.3 A Vision for Big Data in 2020 -- 1.3.1 Transformation of Industry Sectors -- 1.4 A Big Data Innovation Ecosystem -- 1.4.1 The Dimensions of European Big Data Ecosystem -- 1.5 Summary -- References -- Chapter 2: The BIG Project -- 2.1 Introduction -- 2.2 Project Mission -- 2.3 Strategic Objectives -- 2.4 Consortium -- 2.5 Stakeholder Engagement -- 2.6 Project Structure -- 2.7 Methodology -- 2.7.1 Technology State of the Art and Sector Analysis -- 2.7.1.1 Technical Working Groups -- 2.7.1.2 Sectorial Forums -- 2.7.2 Cross-Sectorial Roadmapping -- 2.7.2.1 Consolidation -- 2.7.2.2 Mapping -- 2.7.2.3 Temporal Alignment -- 2.8 Big Data Public Private Partnership -- 2.9 Summary -- References -- Part II: The Big Data Value Chain: Enabling and Value Creating Technologies -- Chapter 3: The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches -- 3.1 Introduction -- 3.2 What Is Big Data? -- 3.3 The Big Data Value Chain -- 3.4 Ecosystems -- 3.4.1 Big Data Ecosystems -- 3.4.2 European Big Data Ecosystem -- 3.4.3 Toward a Big Data Ecosystem -- 3.5 Summary -- References -- Chapter 4: Big Data Acquisition -- 4.1 Introduction -- 4.2 Key Insights for Big Data Acquisition -- 4.3 Social and Economic Impact of Big Data Acquisition -- 4.4 Big Data Acquisition: State of the Art -- 4.4.1 Protocols -- 4.4.1.1 AMQP -- 4.4.1.2 Java Message Service -- 4.4.2 Software Tools -- 4.4.2.1 Storm -- 4.4.2.2 S4 -- 4.4.2.3 Kafka -- 4.4.2.4 Flume -- 4.4.2.5 Hadoop -- 4.5 Future Requirements and Emerging Trends for Big Data Acquisition -- 4.6 Sector Case Studies for Big Data Acquisition. , 4.6.1 Health Sector -- 4.6.2 Manufacturing, Retail, and Transport -- 4.6.3 Government, Public, Non-profit -- 4.6.3.1 Tax Collection Area -- 4.6.3.2 Energy Consumption -- 4.6.4 Media and Entertainment -- 4.6.5 Finance and Insurance -- 4.7 Conclusions -- References -- Chapter 5: Big Data Analysis -- 5.1 Introduction -- 5.2 Key Insights for Big Data Analysis -- 5.3 Big Data Analysis State of the Art -- 5.3.1 Large-Scale: Reasoning, Benchmarking, and Machine Learning -- 5.3.1.1 Large-Scale Reasoning -- 5.3.1.2 Benchmarking for Large-Scale Repositories -- 5.3.1.3 Large-Scale Machine Learning -- 5.3.2 Stream Data Processing -- 5.3.2.1 RDF Data Stream Pattern Matching -- 5.3.2.2 Complex Event Processing -- 5.3.3 Use of Linked Data and Semantic Approaches to Big Data Analysis -- 5.3.3.1 Entity Summarization -- 5.3.3.2 Data Abstraction Based on Ontologies and Communication Workflow Patterns -- 5.4 Future Requirements and Emerging Trends for Big Data Analysis -- 5.4.1 Future Requirements for Big Data Analysis -- 5.4.1.1 Next Generation Big Data Technologies -- 5.4.1.2 Simplicity -- 5.4.1.3 Data -- 5.4.1.4 Languages -- 5.4.2 Emerging Paradigms for Big Data Analysis -- 5.4.2.1 Communities -- 5.4.2.2 Academic Impact -- 5.5 Sectors Case Studies for Big Data Analysis -- 5.5.1 Public Sector -- 5.5.1.1 Traffic -- 5.5.1.2 Emergency Response -- 5.5.2 Health -- 5.5.3 Retail -- 5.5.4 Logistics -- 5.5.5 Finance -- 5.6 Conclusions -- References -- Chapter 6: Big Data Curation -- 6.1 Introduction -- 6.2 Key Insights for Big Data Curation -- 6.3 Emerging Requirements for Big Data Curation -- 6.4 Social and Economic Impact of Big Data Curation -- 6.5 Big Data Curation State of the Art -- 6.5.1 Data Curation Platforms -- 6.6 Future Requirements and Emerging Trends for Big Data Curation -- 6.6.1 Future Requirements for Big Data Curation. , 6.6.2 Emerging Paradigms for Big Data Curation -- 6.6.2.1 Social Incentives and Engagement Mechanisms -- 6.6.2.2 Economic Models -- 6.6.2.3 Curation at Scale -- 6.6.2.4 Human-Data Interaction -- 6.6.2.5 Trust -- 6.6.2.6 Standardization and Interoperability -- 6.6.2.7 Data Curation Models -- 6.6.2.8 Unstructured and Structured Data Integration -- 6.7 Sectors Case Studies for Big Data Curation -- 6.7.1 Health and Life Sciences -- 6.7.1.1 ChemSpider -- 6.7.1.2 Protein Data Bank -- 6.7.1.3 FoldIt -- 6.7.2 Media and Entertainment -- 6.7.2.1 Press Association -- 6.7.2.2 The New York Times -- 6.7.3 Retail -- 6.7.3.1 eBay -- 6.7.3.2 Unilever -- 6.8 Conclusions -- References -- Chapter 7: Big Data Storage -- 7.1 Introduction -- 7.2 Key Insights for Big Data Storage -- 7.3 Social and Economic Impact of Big Data Storage -- 7.4 Big Data Storage State-of-the-Art -- 7.4.1 Data Storage Technologies -- 7.4.1.1 NoSQL Databases -- 7.4.1.2 NewSQL Databases -- 7.4.1.3 Big Data Query Platforms -- 7.4.1.4 Cloud Storage -- 7.4.2 Privacy and Security -- 7.4.2.1 Security Best Practices for Non-relational Data Stores -- 7.4.2.2 Secure Data Storage and Transaction Logs -- 7.4.2.3 Cryptographically Enforced Access Control and Secure Communication -- 7.4.2.4 Security and Privacy Challenges for Granular Access Control -- 7.4.2.5 Data Provenance -- 7.4.2.6 Privacy Challenges in Big Data Storage -- 7.5 Future Requirements and Emerging Paradigms for Big Data Storage -- 7.5.1 Future Requirements for Big Data Storage -- 7.5.1.1 Standardized Query Interfaces -- 7.5.1.2 Security and Privacy -- 7.5.1.3 Semantic Data Models -- 7.5.2 Emerging Paradigms for Big Data Storage -- 7.5.2.1 Increased Use of NoSQL Databases -- 7.5.2.2 In-Memory and Column-Oriented Designs -- 7.5.2.3 Convergence with Analytics Frameworks -- 7.5.2.4 The Data Hub -- 7.6 Sector Case Studies for Big Data Storage. , 7.6.1 Health Sector: Social Media-Based Medication Intelligence -- 7.6.2 Finance Sector: Centralized Data Hub -- 7.6.3 Energy: Device Level Metering -- 7.7 Conclusions -- References -- Chapter 8: Big Data Usage -- 8.1 Introduction -- 8.2 Key Insights for Big Data Usage -- 8.3 Social and Economic Impact for Big Data Usage -- 8.4 Big Data Usage State-of-the-Art -- 8.4.1 Big Data Usage Technology Stacks -- 8.4.1.1 Trade-Offs in Big Data Usage Technologies -- 8.4.2 Decision Support -- 8.4.3 Predictive Analysis -- 8.4.3.1 New Business Model -- 8.4.4 Exploration -- 8.4.5 Iterative Analysis -- 8.4.6 Visualization -- 8.4.6.1 Visual Analytics -- 8.5 Future Requirements and Emerging Trends for Big Data Usage -- 8.5.1 Future Requirements for Big Data Usage -- 8.5.1.1 Specific Requirements -- 8.5.1.2 Industry 4.0 -- 8.5.1.3 Iterative Data Streams -- 8.5.1.4 Visualization -- 8.5.2 Emerging Paradigms for Big Data Usage -- 8.5.2.1 Smart Data -- 8.5.2.2 Big Data Usage in an Integrated and Service-Based Environment -- 8.5.2.3 Service Integration -- 8.5.2.4 Complex Exploration -- 8.6 Sectors Case Studies for Big Data Usage -- 8.6.1 Healthcare: Clinical Decision Support -- 8.6.2 Public Sector: Monitoring and Supervision of Online Gambling Operators -- 8.6.3 Telco, Media, and Entertainment: Dynamic Bandwidth Increase -- 8.6.4 Manufacturing: Predictive Analysis -- 8.7 Conclusions -- References -- Part III: Usage and Exploitation of Big Data -- Chapter 9: Big Data-Driven Innovation in Industrial Sectors -- 9.1 Introduction -- 9.2 Big Data-Driven Innovation -- 9.3 Transformation in Sectors -- 9.3.1 Healthcare -- 9.3.2 Public Sector -- 9.3.3 Finance and Insurance -- 9.3.4 Energy and Transport -- 9.3.5 Media and Entertainment -- 9.3.6 Telecommunication -- 9.3.7 Retail -- 9.3.8 Manufacturing -- 9.4 Discussion and Analysis -- 9.5 Conclusion and Recommendations -- References. , Chapter 10: Big Data in the Health Sector -- 10.1 Introduction -- 10.2 Analysis of Industrial Needs in the Health Sector -- 10.3 Potential Big Data Applications for Health -- 10.4 Drivers and Constraints for Big Data in Health -- 10.4.1 Drivers -- 10.4.2 Constraints -- 10.5 Available Health Data Resources -- 10.6 Health Sector Requirements -- 10.6.1 Non-technical Requirements -- 10.6.2 Technical Requirements -- 10.7 Technology Roadmap for Big Data in the Health Sector -- 10.7.1 Semantic Data Enrichment -- 10.7.2 Data Sharing and Integration -- 10.7.3 Data Privacy and Security -- 10.7.4 Data Quality -- 10.8 Conclusion and Recommendations for Health Sector -- References -- Chapter 11: Big Data in the Public Sector -- 11.1 Introduction -- 11.1.1 Big Data for the Public Sector -- 11.1.2 Market Impact of Big Data -- 11.2 Analysis of Industrial Needs in the Public Sector -- 11.3 Potential Big Data Applications for the Public Sector -- 11.4 Drivers and Constraints for Big Data in the Public Sector -- 11.4.1 Drivers -- 11.4.2 Constraints -- 11.5 Available Public Sector Data Resources -- 11.6 Public Sector Requirements -- 11.6.1 Non-technical Requirements -- 11.6.2 Technical Requirements -- 11.7 Technology Roadmap for Big Data in the Public Sector -- 11.7.1 Pattern Discovery -- 11.7.2 Data Sharing/Data Integration -- 11.7.3 Real-Time Insights -- 11.7.4 Data Security and Privacy -- 11.7.5 Real-Time Data Transmission -- 11.7.6 Natural Language Analytics -- 11.7.7 Predictive Analytics -- 11.7.8 Modelling and Simulation -- 11.8 Conclusion and Recommendations for the Public Sector -- References -- Chapter 12: Big Data in the Finance and Insurance Sectors -- 12.1 Introduction -- 12.1.1 Market Impact of Big Data -- 12.2 Analysis of Industrial Needs in the Finance and Insurance Sectors -- 12.3 Potential Big Data Applications in Finance and Insurance. , 12.4 Drivers and Constraints for Big Data in the Finance and Insurance Sectors.
    Additional Edition: Print version: Cavanillas, José María New Horizons for a Data-Driven Economy Cham : Springer International Publishing AG,c2016 ISBN 9783319215686
    Language: English
    Keywords: Electronic books.
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  • 9
    UID:
    kobvindex_HPB948834920
    Format: 1 online resource (XX, 303 pages 34 illustrations) : , online resource
    Edition: 1st ed. 2016.
    ISBN: 9783319215693 , 3319215698 , 9783319215686 , 331921568X , 9783319460307 , 3319460307 , 9783319460314 , 3319460315
    Content: 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 Research" identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment
    Note: Part I: The Big Data Opportunity -- The Big Data Value Opportunity -- Introduction to the BIG Project -- Part II: The Big Data Value Chain: Enabling and Value Creating Technologies -- The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches -- Big Data Acquisition -- Big Data Analysis -- Big Data Curation -- Big Data Storage -- Big Data Usage -- Part III: Usage and Exploitation of Big Data -- Big Data Driven Innovation in Industrial Sectors -- Big Data in the Health Sector -- Big Data in the Public Sector -- Big Data in the Finance and Insurance Sectors -- Big Data in the Energy and Transport Sectors -- Big Data in the Media and Entertainment Sectors -- Part IV: A Roadmap for Big Data Research -- Cross-Sectorial Requirements Analysis for Big Data Research -- New Horizons for a Data-Driven Economy: Roadmaps and Action Plans for Technology, Businesses, Policy, and Society. , English.
    Additional Edition: Printed edition: 9783319215686
    Language: English
    Keywords: Electronic books. ; Electronic books.
    URL: OAPEN
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    UID:
    almahu_9947389247602882
    Format: XX, 303 p. 34 illus. , online resource.
    Edition: 1st ed. 2016.
    ISBN: 9783319215693
    Content: 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 Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment. .
    Note: Part I: The Big Data Opportunity -- The Big Data Value Opportunity -- Introduction to the BIG Project -- Part II: The Big Data Value Chain: Enabling and Value Creating Technologies -- The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches -- Big Data Acquisition -- Big Data Analysis -- Big Data Curation -- Big Data Storage -- Big Data Usage -- Part III: Usage and Exploitation of Big Data -- Big Data Driven Innovation in Industrial Sectors -- Big Data in the Health Sector -- Big Data in the Public Sector -- Big Data in the Finance and Insurance Sectors -- Big Data in the Energy and Transport Sectors -- Big Data in the Media and Entertainment Sectors -- Part IV: A Roadmap for Big Data Research -- Cross-Sectorial Requirements Analysis for Big Data Research -- New Horizons for a Data-Driven Economy: Roadmaps and Action Plans for Technology, Businesses, Policy, and Society. .
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783319215686
    Language: English
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