Obtaining value from big data for service systems. Volume 1, Big data management / Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, William H. Money.

Format:

Book

Author/Creator:

Kaisler, Stephen H. (Stephen Hendrick), author.

Armour, Frank, author.

Espinosa, J. Alberto, author.

Money, William H., author.

Series:

Service systems and innovations in business and society collection. 2326-2699

Service systems and innovations in business and society collection, 2326-2699

Language:

English

Subjects (All):

Service-oriented architecture (Computer science).

Big data.

Physical Description:

1 online volume (137 pages)

Edition:

2nd edition.

Place of Publication:

New York : Business Expert Press, 2019.

Summary:

Volume I of this two-volume series focuses on the role of big data in service delivery systems. It discusses the definition and orientation to big data, applications of it in service delivery systems, how to obtain results that can affect/enhance service delivery, and how to build an effective big data organization. This volume will assist readers in fitting big data analysis into their service-based organizations. It will also help readers understand how to improve the use of big data to enhance their service-oriented organizations.

Contents:

Cover

Obtaining Value from Big Data for Service Systems, Volume I: Big Data Management

Dedication

Contents

Purpose

Acknowledgments

List of Acronyms

Chapter 1: Introduction

Defining Big Data

Getting Started with Big Data

Adding Value to Organizations

Outline of This Book

Chapter 2: Applications of Big Data to Service Delivery

Defining Services

Service Systems

Big Data in Service Delivery

A Service Delivery Model

Supporting Service Delivery with Big Data

Data-Driven Companies

Retail Analytics

Health Care

Fraud Detection

Mass Transit

Chapter 3: Analyzing Big Data for Successful Results

Big Data Usage

Big Data Analytics

Big Data Analytics Initiatives Need a Process

The Analytics Cycle

Analytic Modeling Methods and Approaches

Quantitative Analysis

Qualitative Analysis

Emerging Analytics Application Areas

Sentiment Analysis

Geospatial Analytics

Unstructured Text Processing

Image, Video, and Audio Processing

Edge and Location-Specific Analytics

Network Analytics

Cognitive Analytics

Key Challenges for Analytics

Analytical Resource and Tool Survey

Commercial Packages

Open Source Packages

Chapter 4: Building an Effective Big Data Organization

Organizational Design and Practices

Enterprise, Domain, and Application Architecture

Business Architecture for Analytics

Business Architecture (BA) Aligns Analytics Initiatives and Business Outcomes

Analytics Body of Knowledge Focus

Governanc

Big Data Analytics Culture

Big Data Analytics Maturity

People

Chief Data Officer/Chief Information Officer

Chief Knowledge Officer

Chief Analytic Officer

Chief Portfolio Integration Manager

Analytically Informed Business Managers

Data Analyst

Data Scientist

Big Data Technologist-Infrastructure and Tools.

Talent Identification and Acquisition-Staffing the Analytics Operation

Hiring Trained Staff

Communication, Organizational Skills, and Knowledge

In-House Training

College and University Education Programs

Commercial Education Opportunities

Outsourcing the Big Data Analytics Function

Big Data Analytics Teamwork

Distributed Analytics-Analytics within the Business Unit

Centralized Analytics Group

Analytics Group within the IT Department

Distributed Analytics Groups within the IT and Business Units

APPENDIX: Methods-Based Analytics Taxonomy

References

Further Reading

Glossary

About the Contributors

Index

Ad Page

Back Cover.

ISBN:

1-949443-56-6