TY  - BOOK
AU  - Williams , Steve
TI  - Business intelligence strategy and big data analytics: a general management perspective
SN  - 9780128091982
U1  - 658.472 
PY  - 2016///
CY  - Cambridge
PB  - Morgan Kaufmann
KW  - Big data
KW  - Business intelligence
KW  - Business planning
KW  - Industrial management
KW  - Strategic planning
N1  - Table of content

About the Author

Foreword

Acknowledgments

Introduction

The Challenge of Formulating Business Intelligence Strategy
Overview of the Book
Organization of the Book
Closing the Loop
Chapter 1. The Personal Face of Business Intelligence

Abstract
1.1 BI Case Study Setting
1.2 BBF BI Opportunities
1.3 The BBF BI Vision and BI Opportunity Portfolio & Business Case
1.4 Generalizing from the BBF Case—BI Applications for Manufacturers
1.5 Lessons Learned for BI Strategy—BBF BI Progress
1.6 Questions to Consider for Your Company or Function
Chapter 2. Business Intelligence in the Era of Big Data and Cognitive Business

Abstract
2.1 Getting Clear About Terminology—Business Definitions of Business Intelligence and Related Terms
2.2 The Hype Around BI, Big Data, Analytics, and Cognitive Business
2.3 A Business View of Big Data
2.4 A Business View of Cognitive Business
2.5 BI and Analytics—Is There a Difference?
2.6 Beyond the Hype—What BI Success Looks Like
2.7 Summary—Industry Views of BI Success
2.8 Recap of Some Key Points
Chapter 3. The Strategic Importance of Business Intelligence

Abstract
3.1 A Business View of BI
3.2 How BI Enhances Business Processes and Business Performance
3.3 The Strategic Importance of BI
3.4 Skill Development Opportunity: The Strategic Importance of BI
3.5 Summary of Some Key Points
Chapter 4. BI Opportunity Analysis

Abstract
4.1 BI Opportunity Analysis Provides the Economic Rationale for BI
4.2 Top-Down BI Opportunity Analysis
4.3 Using Strategy Maps to Discover Bios
4.4 Using Structured Interviews to Discover BIOs
4.5 Factoring in Big Data and Cognitive Business Opportunities
4.6 Documenting BIOs
4.7 Skill Improvement Opportunity: Discovering BIOs and Mapping to BI Styles
4.8 Summary of Some Key Points
Chapter 5. Prioritizing BI Opportunities (BIOs)

Abstract
5.1 BI Portfolio Planning and the BI Portfolio Map
5.2 Factors to Consider When Prioritizing BIOs
5.3 Approaches to Prioritizing BIOs
5.4 Skill Development Opportunity: Develop and Justify a BI Portfolio Map
5.5 Summary of Some Key Points
Chapter 6. Leveraging BI for Performance Management, Process Improvement, and Decision Support

Abstract
6.1 BI as a Key Enabler of BPM
6.2 BI as a Key Enabler of Business Process Improvement
6.3 BI as a Key Enabler of High-Impact Business Decisions
6.4 Skill Development Opportunity
6.5 Summary of Some Key Points
Chapter 7. Meeting the Challenges of Enterprise BI

Abstract
7.1 A General Management View About BI Success
7.2 Challenges for BI Success
7.3 Organizational Design for BI Success
7.4 Skill Development Opportunity: Assess BI Challenges, Risks, and Barriers
7.5 Summary of Some Key Points
Chapter 8. General Management Perspectives on Technical Topics

Abstract
8.1 The Technical Landscape for BI Program Execution
8.2 Technical Infrastructure for BI
8.3 Data Infrastructure for BI
8.4 BI and the Cloud
8.5 Summary
N2  - Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability.  It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion.  Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others.  It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like “big data” and “big data analytics” have been introduced into the business and technical lexicon.  Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness.  Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate.  More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both
ER  -