Data control : (Record no. 80439)

000 -LEADER
fixed length control field 05536nam a22003257a 4500
003 - CONTROL NUMBER IDENTIFIER
control field CITU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230213104234.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr an aaaaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 211118b ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781786305503
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119779780
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.7
100 1# - MAIN ENTRY--PERSONAL NAME
Preferred name for the person Monino, Jean-Louis.
Relator term author
245 ## - TITLE STATEMENT
Title Data control :
Remainder of title major challenge for the digital society /
Statement of responsibility, etc Jean-Lous Monino.
264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc London :
Name of publisher, distributor, etc ISTE, Ltd.,
Date of publication, distribution, etc 2020.
264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Hoboken :
Name of publisher, distributor, etc Wiley,
Date of publication, distribution, etc 2020.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (214 pages) :
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term computer
Media type code c
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term online resource
Carrier type code cr
500 ## - GENERAL NOTE
General note ABOUT THE AUTHOR<br/>Jean-Louis Monino is a Researcher at the Montpellier Recherche en Economie laboratory, Emeritus Professor at the University of Montpellier, and Head of the Traitement et Recherche de l'Information et de la Statistique laboratory in France. His research focuses on data processing, econometrics, statistics, data mining, forecast techniques and economic intelligence.
505 0# - CONTENTS
Formatted contents note TABLE OF CONTENTS<br/>Foreword ix<br/><br/>Acknowledgements xiii<br/><br/>Introduction xv<br/><br/>Chapter 1. From Data to Decision-Making: A Major Pathway 1<br/><br/>1.1. Background on economic intelligence 2<br/><br/>1.2. Strategic economic intelligence revisited 3<br/><br/>1.2.1. The three major steps for decision support 3<br/><br/>1.2.2. Modeling the concept of strategic business intelligence 4<br/><br/>1.3. Conclusion 9<br/><br/>Chapter 2. Data: An Indispensable Platform for Companies 11<br/><br/>2.1. The key figures of digital technology 14<br/><br/>2.1.1. Figures on social networks 20<br/><br/>2.1.2. Numbers: Big Data 22<br/><br/>2.1.3. Key figures: the Internet of Things 24<br/><br/>2.2. The power of data: a major challenge 28<br/><br/>2.3. The Big Data revolution, “Mega Data” 30<br/><br/>2.3.1. Understanding the world of Big Data 31<br/><br/>2.3.2. Open data: a new challenge 41<br/><br/>2.4. Developing the culture of data sharing 55<br/><br/>2.5. Storage of data in databases 56<br/><br/>2.6. The appearance of buzzwords: Big, Open, Viz, etc. 58<br/><br/>2.7. Conclusion 59<br/><br/>Chapter 3. From Data to Information: Essential Transformations 63<br/><br/>3.1. Value creation from data processing 63<br/><br/>3.2. Value creation and analysis of open databases 69<br/><br/>3.3. From data to information: the “DataViz” or data visualization 73<br/><br/>3.4. From data to information: statistical processing 74<br/><br/>3.4.1. Phases of data processing 75<br/><br/>3.4.2. Processing the data 75<br/><br/>3.5. Turning mass data into an opportunity for innovation 81<br/><br/>3.6. Development of company assets in the web of data 87<br/><br/>3.7. Conclusion 91<br/><br/>Chapter 4. Information: Contextualized and Materialized Data 93<br/><br/>4.1. What is information? 94<br/><br/>4.1.1. How can we define information? 94<br/><br/>4.2. Internal and external information 100<br/><br/>4.2.1. Internal information 100<br/><br/>4.2.2. External information 100<br/><br/>4.3. Formal and informal information 100<br/><br/>4.3.1. Formal information 100<br/><br/>4.3.2. Informal information 101<br/><br/>4.4. Importance of information 101<br/><br/>4.4.1. White information 101<br/><br/>4.4.2. Gray information 101<br/><br/>4.4.3. Black information 101<br/><br/>4.5. Décodex set up by Le Monde 102<br/><br/>4.6. Conclusion 103<br/><br/>Chapter 5. From Information to Knowledge: Valuing and Innovating 105<br/><br/>5.1. Innovation as a driving force of growth 105<br/><br/>5.1.1. Innovation and the intangible economy 106<br/><br/>5.2. Knowledge: the key to innovation 108<br/><br/>5.3. Building knowledge: economic intelligence 109<br/><br/>5.3.1. The EI process and the transition from information to knowledge 110<br/><br/>5.3.2. Managing the data warehouse to extract knowledge and insight 111<br/><br/>5.4. Data mining, Statistica and Tibco 114<br/><br/>5.5. Information an economic good? 115<br/><br/>5.5.1. Innovation as a driving force of growth 115<br/><br/>5.5.2. Strategic business intelligence 116<br/><br/>5.6. What is data science? 118<br/><br/>5.7. Conclusion 119<br/><br/>Chapter 6. From Knowledge to Strategic Business Intelligence: Decision-Making 121<br/><br/>6.1. Data valuation mechanisms 121<br/><br/>6.2. How do you value data? 122<br/><br/>6.3. Data governance: a key factor in valuation 132<br/><br/>6.4. EI: protection and enhancement of digital heritage 138<br/><br/>6.5. Data analysis techniques: data mining/text mining 143<br/><br/>6.6. Conclusion 148<br/><br/>Conclusion 151<br/><br/>Glossary 157<br/><br/>References 159<br/><br/>Index 173
520 ## - SUMMARY, ETC.
Summary, etc Businesses are becoming increasingly aware of the importance of data and information. As such, they are eager to develop ways to “manage” them, to enrich them and take advantage of them. Indeed, the recent explosion of a phenomenal amount of data, and the need to analyze it, brings to the forefront the well-known hierarchical model: “Data, Information, Knowledge”.<br/>“Data”– this new intangible manna – is produced in real time. It arrives in a continuous stream and comes from a multitude of sources that are generally heterogeneous. This accumulation of data of all kinds is generating new activities designed to analyze these huge amounts of information. It is therefore necessary to adapt and try new approaches, methods, new knowledge and new ways of working. This leads to new properties and new issues as a logical reference must be created and implemented. At the company level, this mass of data is difficult to manage; interpreting it is the predominant challenge.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big data.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business
General subdivision Data processing.
655 #0 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
856 ## - ELECTRONIC LOCATION AND ACCESS
Link text Full text available at Wiley Online Library Click here to view
Uniform Resource Identifier https://onlinelibrary.wiley.com/doi/book/10.1002/9781119779780
942 ## - ADDED ENTRY ELEMENTS
Source of classification or shelving scheme
Item type EBOOK
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Date acquired Source of acquisition Inventory number Full call number Barcode Date last seen Price effective from Item type
          COLLEGE LIBRARY COLLEGE LIBRARY 2021-11-18 ALBASA 50881 005.7 M748 2020 CL-50881 2021-11-18 2021-11-18 EBOOK