The Data Industry
(Sprache: Englisch)
Provides an introduction of the data industry to the field of economics
This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry....
This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry....
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Provides an introduction of the data industry to the field of economicsThis book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises' business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees.
* Defines and develops the concept of a "Data Industry," and explains the economics of data to data scientists and statisticians
* Includes numerous case studies and examples from a variety of industries and disciplines
* Serves as a useful guide for practitioners and entrepreneurs in the business of data technology
The Data Industry: The Business and Economics of Information and Big Data is a resource for practitioners in the data science industry, government, and students in economics, business, and statistics.
CHUNLEI TANG, Ph.D., is a research fellow at Harvard University. She is the co-founder of Fudan's Institute for Data Industry and proposed the concept of the "data industry". She received a Ph.D. in Computer and Software Theory in 2012 and a Master of Software Engineering in 2006 from Fudan University, Shanghai, China.
Inhaltsverzeichnis zu „The Data Industry “
Bibliography IDedication II
Praise III
Preface IV
Chapter I What Is Data Industry? 1
1.1 Data 2
1.1.1 Data Resources 2
1.1.2 The Data Asset 4
1.2 Industry 6
1.2.1 Classification of Industries 6
1.2.2 The Modern Industrial System 7
1.3 Data Industry 10
1.3.1 Definitions 10
1.3.2 An Industry Structure Study 11
1.3.3 Industrial Behavior 13
1.3.4 Market Performance 17
Chapter II Data Resources 20
2.1 Scientific Data 20
2.1.1 Data-Intensive Discovery in the Natural Science 20
2.1.2 The Social Sciences Revolution 21
2.1.3 The Underused Scientific Record 23
2.2 Administrative Data 23
2.2.1 Open Governmental Affairs Data 25
2.2.2 Public Release of Administrative Data 26
2.2.3 A "Numerical" Misunderstanding in Governmental Affairs 27
2.3 Internet Data 28
2.3.1 Cyberspace: Data of the Sole Existence 28
2.3.2 Crawled Fortune 29
2.3.3 Forum Opinion Mining 30
2.3.4 Chat with Hidden Identities 31
2.3.5 Email: The First Type of Electronic Evidence 31
2.3.6 Evolution of the Blog 33
2.3.7 Six Degrees Social Network 34
2.4 Financial Data 34
2.4.1 Twins on News and Financial Data 35
2.4.2 The Annoyed Data Center 35
2.5 Health Data 36
2.5.1 Clinical Data: EMRs, EHRs, and PHRs 36
2.5.2 Claims Data and Medicare Fraud or Abuse Detection 37
2.6 Transportation Data 38
2.6.1 Trajectory Data 39
2.6.1 Fixed-position Data 39
2.6.3 Location-based Data 40
2.7 Transaction Data 41
2.7.1 Receipts Data 41
2.7.2 E-commerce Data 42
Chapter III Data Industry Chain 44
3.1 Industrial Chain Definition 44
3.1.1 The Meaning and Characteristics 44
3.1.2 Category Attributes
... mehr
46
3.2 Industrial Chain Structure 46
3.2.1 Economic Entities 47
3.2.2 Environmental Elements 48
3.3 Industrial Chain Formation 49
3.3.1 Value Analysis 49
3.3.2 Dimensional Matching 54
3.4 Evolution of Industrial Chain Management 55
3.5 Industrial Chain Governance 57
3.5.1 Governance Patterns 58
3.5.2 Instruments of Governance 59
3.6 The Data Industry Chain and Its Innovation Network 61
3.6.1 Innovation Layers 61
3.6.2 Supporting Systems 62
Chapter IV Existing Data Innovations 64
4.1 Web Creations 64
4.1.1 Network Writing 64
4.1.2 Creative Designs 66
4.1.3 Bespoke Development 67
4.1.4 Crowdsourcing 67
4.2 Data Marketing 68
4.2.1 Market Positioning 69
4.2.2 Business Insights 70
4.2.3 Customer Evaluation 71
4.3 Push Services 72
4.3.1 Targeted Advertising 73
4.3.2 Instant Broadcasting 74
4.4 Price Comparison 75
4.5 Disease Prevention 76
4.5.1 Tracking Epidemics 77
4.5.2 Whole-Genome Sequencing 78
Chapter V Data Services in Multiple Domains 79
5.1 Scientific Data Services 79
5.1.1 Literature Search Reform 79
5.1.2 An Alternative Scholarly Communication Initiative 80
5.1.3 Scientific Research Project Services 81
5.2 Administrative Data Services 83
5.2.1 Police Department 83
5.2.2 Statistical Office 84
5.2.3 Environmental Protection Agency 85
5.3 Internet Data Services 86<
3.2 Industrial Chain Structure 46
3.2.1 Economic Entities 47
3.2.2 Environmental Elements 48
3.3 Industrial Chain Formation 49
3.3.1 Value Analysis 49
3.3.2 Dimensional Matching 54
3.4 Evolution of Industrial Chain Management 55
3.5 Industrial Chain Governance 57
3.5.1 Governance Patterns 58
3.5.2 Instruments of Governance 59
3.6 The Data Industry Chain and Its Innovation Network 61
3.6.1 Innovation Layers 61
3.6.2 Supporting Systems 62
Chapter IV Existing Data Innovations 64
4.1 Web Creations 64
4.1.1 Network Writing 64
4.1.2 Creative Designs 66
4.1.3 Bespoke Development 67
4.1.4 Crowdsourcing 67
4.2 Data Marketing 68
4.2.1 Market Positioning 69
4.2.2 Business Insights 70
4.2.3 Customer Evaluation 71
4.3 Push Services 72
4.3.1 Targeted Advertising 73
4.3.2 Instant Broadcasting 74
4.4 Price Comparison 75
4.5 Disease Prevention 76
4.5.1 Tracking Epidemics 77
4.5.2 Whole-Genome Sequencing 78
Chapter V Data Services in Multiple Domains 79
5.1 Scientific Data Services 79
5.1.1 Literature Search Reform 79
5.1.2 An Alternative Scholarly Communication Initiative 80
5.1.3 Scientific Research Project Services 81
5.2 Administrative Data Services 83
5.2.1 Police Department 83
5.2.2 Statistical Office 84
5.2.3 Environmental Protection Agency 85
5.3 Internet Data Services 86<
... weniger
Autoren-Porträt von Chunlei Tang
CHUNLEI TANG, Ph.D., is a research fellow at Harvard University. She is the co-founder of Fudan's Institute for Data Industry and proposed the concept of the "data industry". She received a Ph.D. in Computer and Software Theory in 2012 and a Master of Software Engineering in 2006 from Fudan University, Shanghai, China.
Bibliographische Angaben
- Autor: Chunlei Tang
- 2016, 1. Auflage, 216 Seiten, Maße: 15 x 21 cm, Gebunden, Englisch
- Verlag: Wiley & Sons
- ISBN-10: 111913840X
- ISBN-13: 9781119138402
- Erscheinungsdatum: 08.07.2016
Sprache:
Englisch
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