Data Science and Digital Business. (2019)
- Record Type:
- Book
- Title:
- Data Science and Digital Business. (2019)
- Main Title:
- Data Science and Digital Business
- Further Information:
- Note: Editors, Fausto Pedro García Márquez and Benjamin Lev.
- Other Names:
- García Márquez, Fausto Pedro
Lev, Benjamin - Contents:
- Intro; Contents; About the Editors; Introduction to Data Science and Digital Business; Data Management and Visualization Using Big Data Analytics; 1 Introduction to Data Sciences; 2 Data Management Methodologies; 2.1 Business Understanding; 2.2 Analytical Approach in Use; 2.3 Agile Kanban; 3 Real World Cases; 3.1 Case Study: Maritime Pattern Identification and Route Reconstruction; 3.2 Case Study: Understanding Lifestyles in Distinct Cities with Social Media Data Analysis; 4 Applications of Big Data Analytics; 4.1 Big Data in Healthcare; 4.2 Big Data and the World of Finance 4.3 Big Data in Social Media Analytics4.4 Big Data for the Telecom Industry; 5 Data Visualization Using Analytical Tools; 5.1 Data Wrangler; 5.2 The R Project; 5.3 Tableau Plateau; 5.4 MINITAB Software; 5.5 SPSS; 6 Conclusion; References; Data Science and Digital Business; 1 Introduction; 2 Background; 2.1 Modeling of Storm Surge and Inundation; 2.2 Risk Analyses in Hurricane Studies; 3 Methodology; 3.1 Study Area Description; 3.2 Datasets; 4 Risk Related Data and Visualization; 4.1 Population and Traffic Data; 4.2 Elevation and Direct Loss Coverage Data; 4.3 Hurricane Storm Surge Data 4.4 Flood Inundation5 Risk Analyses and Prediction; 5.1 Collinearity Analysis and Multiple Regression Analysis; 5.2 Risk Prediction; 6 Conclusions; References; Data Science and Conversational Interfaces: A New Revolution in Digital Business; 1 Introduction; 2 Defining Conversational Interfaces; 3 Natural LanguageIntro; Contents; About the Editors; Introduction to Data Science and Digital Business; Data Management and Visualization Using Big Data Analytics; 1 Introduction to Data Sciences; 2 Data Management Methodologies; 2.1 Business Understanding; 2.2 Analytical Approach in Use; 2.3 Agile Kanban; 3 Real World Cases; 3.1 Case Study: Maritime Pattern Identification and Route Reconstruction; 3.2 Case Study: Understanding Lifestyles in Distinct Cities with Social Media Data Analysis; 4 Applications of Big Data Analytics; 4.1 Big Data in Healthcare; 4.2 Big Data and the World of Finance 4.3 Big Data in Social Media Analytics4.4 Big Data for the Telecom Industry; 5 Data Visualization Using Analytical Tools; 5.1 Data Wrangler; 5.2 The R Project; 5.3 Tableau Plateau; 5.4 MINITAB Software; 5.5 SPSS; 6 Conclusion; References; Data Science and Digital Business; 1 Introduction; 2 Background; 2.1 Modeling of Storm Surge and Inundation; 2.2 Risk Analyses in Hurricane Studies; 3 Methodology; 3.1 Study Area Description; 3.2 Datasets; 4 Risk Related Data and Visualization; 4.1 Population and Traffic Data; 4.2 Elevation and Direct Loss Coverage Data; 4.3 Hurricane Storm Surge Data 4.4 Flood Inundation5 Risk Analyses and Prediction; 5.1 Collinearity Analysis and Multiple Regression Analysis; 5.2 Risk Prediction; 6 Conclusions; References; Data Science and Conversational Interfaces: A New Revolution in Digital Business; 1 Introduction; 2 Defining Conversational Interfaces; 3 Natural Language Understanding; 4 Dialog Management; 5 Natural Language Generation; 6 Main Conclusions; References; After 2017: Managers Exit and Banks Arise; 1 Introduction; 1.1 Blockchain Technology and Smart Contract; 2 Models of Managements; 3 Banks as Economic Agent; 4 Discussions 5 ConclusionsReferences; Synergies Between Association Rules and Collaborative Filtering in Recommender System: An Application to Auto Industry; 1 Introduction; 2 Literature Review; 2.1 Collaborative Filtering (CF) Method; 2.2 Content-Based (CB) Method; 3 The Framework of Recommender System; 3.1 General Introduction to the Proposed Recommender System; 3.2 Data Pre-processing; 3.3 Recommendation Process; 3.4 Evaluation; 4 Application of Auto Industry; 4.1 Problem Description; 4.2 Deployment; 4.3 Result Analysis; 5 Conclusion and Future Work; References Information Security Research Challenges in the Process of Digitizing Business: A Review Based on the Information Security Model of IBM1 Introduction; 2 Review Method; 2.1 Core ISec Themes: IBM ISec Capability Reference Model; 2.2 Journal Selection and Paper Identification; 2.3 Coding Methods; 3 Overview of ISec Research; 3.1 Papers Distributions by Journal and Period; 3.2 Contribution of ISec Research to Industry Requirements; 3.3 Main Theories and Methods Conducted in Each Theme; 4 Research Streams Summary; 4.1 Governance; 4.2 Personnel Security; 4.3 Threat Mitigation; 4.4 ISec Economics … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2019
- Extent:
- 1 online resource
- Subjects:
- 658.40301
Operations research
Big data
Management information systems
Statistics
Engineering economy
BUSINESS & ECONOMICS / Industrial Management
BUSINESS & ECONOMICS / Management
BUSINESS & ECONOMICS / Management Science
BUSINESS & ECONOMICS / Organizational Behavior
Electronic books - Languages:
- English
- ISBNs:
- 9783319956510
3319956515 - Related ISBNs:
- 9783319956503
- Notes:
- Note: Includes bibliographical references.
Note: Online resource; title from PDF file page (EBSCO, viewed January 10, 2019). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.382503
- Ingest File:
- 02_367.xml