Analytics and Knowledge Management: 1st Edition (Hardback) book cover

Analytics and Knowledge Management

1st Edition

Edited by Suliman Hawamdeh, Hsia-Ching Chang

Auerbach Publications

446 pages | 10 Color Illus. | 15 B/W Illus.

Purchasing Options:$ = USD
Hardback: 9781138630260
pub: 2018-05-16
$119.95
x
eBook (VitalSource) : 9781315209555
pub: 2018-08-06
from $44.98


FREE Standard Shipping!

Description

The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations.

The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics.

Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics.

Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships.

This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms.

Table of Contents

1 Knowledge Management for Action-Oriented Analytics

[JOHN S. EDWARDS AND EDUARDO RODRIGUEZ]

2 Data Analytics Process: An Application Case on Predicting

Student Attrition

[DURSUN DELEN]

3 Transforming Knowledge Sharing in Twitter-Based Communities

Using Social Media Analytics

[NICHOLAS EVANGELOPOULOS, SHADI SHAKERI,

AND ANDREA R. BENNETT]

4 Data Analytics for Deriving Knowledge from User Feedback

[KULJIT KAUR CHAHAL AND SALIL VISHNU KAPUR]

5 Relating Big Data and Data Science to the Wider Concept

of Knowledge Management

[HILLARY STARK AND SULIMAN HAWAMDEH]

6 Fundamentals of Data Science for Future Data Scientists

[JIANGPING CHEN, BRENDA REYES AYALA, DUHA ALSMADI,

AND GUONAN WANG]

7 Social Media Analytics

[MIYOUNG CHONG AND HSIA-CHING CHANG]

8 Transactional Value Analytics in Organizational Development

[CHRISTIAN STARY]

9 Data Visualization Practices and Principles

[JEONGHYUN KIM AND ERIC R. SCHULER]

10 Analytics Using Machine Learning-Guided Simulations with

Application to Healthcare Scenarios

[MAHMOUD ELBATTAH AND OWEN MOLLOY]

11 Intangible Dynamics: Knowledge Assets in the Context

of Big Data and Business Intelligence

[G. SCOTT ERICKSON AND HELEN N. ROTHBERG]

12 Analyzing Data and Words—Guiding Principles and Lessons

Learned

[DENISE A. D. BEDFORD]

13 Data Analytics for Cyber Threat Intelligence

[HONGMEI CHI, ANGELA R. MARTIN, AND CAROL Y. SCARLETT]

About the Editors

Suliman Hawamdeh is a professor and department chair of the Department of Information Science in the College of Information at the University of North Texas. He is the director of the Information Science PhD program, one of the largest interdisciplinary information science PhD programs in the country. He is the editor in chief of the Journal of Information and Knowledge Management (JIKM) and the editor of a book series on innovation and knowledge management published by World Scientific. Dr. Hawamdeh founded and directed several academic programs including the first Master of Science in Knowledge Management in Asia at the School of Communication and Information at Nanyang Technological University in Singapore. Dr. Hawamdeh has extensive industrial experience. He was the Managing Director of ITC Information Technology Consultant Ltd, a company that developed and marketed a line of software development products. He worked as a consultant to several organizations including NEC, Institute of Southeast Asian Studies, Petronas, and Shell. Dr. Hawamdeh has authored and edited several books on knowledge management including Information and Knowledge Society published by McGraw Hill and Knowledge Management: Cultivating the Knowledge Professionals Published by Chandos Publishing, as well as several edited and co-edited books published by World Scientific.

Hsia-Ching Chang is an assistant professor in the Department of Information Science, College of Information at the University of North Texas. She received her PhD in informatics and MS in information science from the University at Albany, State University of New York as well as her MA in public policy from the National Taipei University in Taiwan. Her research interests concentrate on data analytics, social media, cybersecurity, knowledge mapping, scientometrics, information architecture, and information interaction.

About the Series

Data Analytics Applications

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
COM012000
COMPUTERS / Computer Graphics
COM021030
COMPUTERS / Database Management / Data Mining
MAT029000
MATHEMATICS / Probability & Statistics / General