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Data Science and Digital Business

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Cover of 'Data Science and Digital Business'

Table of Contents

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    Book Overview
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    Chapter 1 Data Management and Visualization Using Big Data Analytics
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    Chapter 2 Data Science and Digital Business
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    Chapter 3 Data Science and Conversational Interfaces: A New Revolution in Digital Business
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    Chapter 4 After 2017: Managers Exit and Banks Arise
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    Chapter 5 Synergies Between Association Rules and Collaborative Filtering in Recommender System: An Application to Auto Industry
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    Chapter 6 Information Security Research Challenges in the Process of Digitizing Business: A Review Based on the Information Security Model of IBM
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    Chapter 7 Deploying a Scalable Data Science Environment Using Docker
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    Chapter 8 Clean up CHAOS and Use E-CRM (A Digital Concept) to Expand the Business: A Case of Pakistan
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    Chapter 9 Furthering Big Data Utilization in Tourism
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    Chapter 10 C-LASSO Estimator for Generalized Additive Logistic Regression Based on B-Spline
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    Chapter 11 An Efficient Bundle-Like Algorithm for Data-Driven Multi-objective Bi-level Signal Design for Traffic Networks with Hazardous Material Transportation
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    Chapter 12 Advanced Regression Models: Least Squares, Nonlinear, Poisson and Binary Logistics Regression Using R
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    Chapter 13 Student Desertion: What Is and How Can It Be Detected on Time?
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    Chapter 14 Bioelectric Potential Plant
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    Chapter 15 False Alarms Management by Data Science
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    Chapter 16 Introduction to Data Science and Digital Business
Overall attention for this book and its chapters
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8 X users

Citations

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Title
Data Science and Digital Business
Published by
Springer International Publishing, January 2019
DOI 10.1007/978-3-319-95651-0
ISBNs
978-3-31-995650-3, 978-3-31-995651-0
Editors

Fausto Pedro García Márquez, Benjamin Lev

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 18%
Researcher 5 10%
Student > Master 5 10%
Student > Ph. D. Student 3 6%
Lecturer 3 6%
Other 10 20%
Unknown 15 30%
Readers by discipline Count As %
Business, Management and Accounting 8 16%
Computer Science 8 16%
Engineering 6 12%
Economics, Econometrics and Finance 3 6%
Social Sciences 2 4%
Other 6 12%
Unknown 17 34%