Data Analytics and AI
1st Edition
Published on 7. August 2020
Book
Hardback
242 pages
978-0-367-52200-1 (ISBN)
Description
Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools?
Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.
Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional Practice & Development
Illustrations
62 s/w Abbildungen, 3 s/w Tabellen
3 Tables, black and white; 62 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 19 mm
Weight
570 gr
ISBN-13
978-0-367-52200-1 (9780367522001)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Jay Liebowitz
Data Analytics and AI
Book
08/2020
1st Edition
CRC Press
€82.70
Shipment within 15-20 days
Person
Dr. Jay Liebowitz is the Distinguished Chair of Applied Business and Finance at Harrisburg University of Science and Technology. He previously was the Orkand Endowed Chair of Management and Technology in the Graduate School at the University of Maryland University College (UMUC). He served as a Professor in the Carey Business School at Johns Hopkins University. He was ranked one of the top 10 knowledge management researchers/practitioners out of 11,000 worldwide, and was ranked second in KM Strategy worldwide according to the January 2010 Journal of Knowledge Management. At Johns Hopkins University, he was the founding Program Director for the Graduate Certificate in Competitive Intelligence and the Capstone Director of the MS-Information and Telecommunications Systems for Business Program, where he engaged over 30 organizations in industry, government, and not-for-profits in capstone projects.
Content
Contents
Foreword..............................................................................................................ix
Preface..............................................................................................................xvii
List of Contributors..........................................................................................xix
1 Unraveling Data Science, Artificial Intelligence, and Autonomy............1
JOHN PIORKOWSKI
2 Unlock the True Power of Data Analytics with Artificial
Intelligence ...........................................................................................21
RITU JYOTI
3 Machine Intelligence and Managerial Decision-Making......................31
LEE SCHLENKER AND MOHAMED MINHAJ
4 Measurement Issues in the Uncanny Valley: The Interaction
between Artificial Intelligence and Data Analytics...............................53
DOUGLAS A. SAMUELSON
5 An Overview of Deep Learning in Industry..........................................65
QUAN LE, LUIS MIRALLES-PECHUAN, SHRIDHAR KULKARNI,
JING SU, AND OISIN BOYDELL
6 Chinese AI Policy and the Path to Global Leadership:
Competition, Protectionism, and Security............................................99
MARK ROBBINS
7 Natural Language Processing in Data Analytics................................117
YUDONG LIU
8 AI in Smart Cities Development: A Perspective of Strategic
Risk Management................................................................................133
EDUARDO RODRIGUEZ AND JOHN S. EDWARDS
9 Predicting Patient Missed Appointments in the Academic
Dental Clinic.......................................................................................151
AUNDREA L. PRICE AND GOPIKRISHNAN CHANDRASEKHARAN
10 Machine Learning in Cognitive Neuroimaging..................................167
SIAMAK ARAM, DENIS KORNEV, YE HAN, MINA EKRAMNIA,
ROOZBEH SADEGHIAN, SAEED ESMAILI SARDARI,
HADIS DASHTESTANI, SAGAR KORA VENU, AND AMIR GANDJBAKHCHE
11 People, Competencies, and Capabilities Are Core Elements
in Digital Transformation: A Case Study of a Digital
Transformation Project at ABB...........................................................183
ISMO LAUKKANEN
12 AI-Informed Analytics Cycle: Reinforcing Concepts..........................211
ROSINA O. WEBER AND MAUREEN P. KINKELA
Index............................................................................................................235
Foreword..............................................................................................................ix
Preface..............................................................................................................xvii
List of Contributors..........................................................................................xix
1 Unraveling Data Science, Artificial Intelligence, and Autonomy............1
JOHN PIORKOWSKI
2 Unlock the True Power of Data Analytics with Artificial
Intelligence ...........................................................................................21
RITU JYOTI
3 Machine Intelligence and Managerial Decision-Making......................31
LEE SCHLENKER AND MOHAMED MINHAJ
4 Measurement Issues in the Uncanny Valley: The Interaction
between Artificial Intelligence and Data Analytics...............................53
DOUGLAS A. SAMUELSON
5 An Overview of Deep Learning in Industry..........................................65
QUAN LE, LUIS MIRALLES-PECHUAN, SHRIDHAR KULKARNI,
JING SU, AND OISIN BOYDELL
6 Chinese AI Policy and the Path to Global Leadership:
Competition, Protectionism, and Security............................................99
MARK ROBBINS
7 Natural Language Processing in Data Analytics................................117
YUDONG LIU
8 AI in Smart Cities Development: A Perspective of Strategic
Risk Management................................................................................133
EDUARDO RODRIGUEZ AND JOHN S. EDWARDS
9 Predicting Patient Missed Appointments in the Academic
Dental Clinic.......................................................................................151
AUNDREA L. PRICE AND GOPIKRISHNAN CHANDRASEKHARAN
10 Machine Learning in Cognitive Neuroimaging..................................167
SIAMAK ARAM, DENIS KORNEV, YE HAN, MINA EKRAMNIA,
ROOZBEH SADEGHIAN, SAEED ESMAILI SARDARI,
HADIS DASHTESTANI, SAGAR KORA VENU, AND AMIR GANDJBAKHCHE
11 People, Competencies, and Capabilities Are Core Elements
in Digital Transformation: A Case Study of a Digital
Transformation Project at ABB...........................................................183
ISMO LAUKKANEN
12 AI-Informed Analytics Cycle: Reinforcing Concepts..........................211
ROSINA O. WEBER AND MAUREEN P. KINKELA
Index............................................................................................................235