Book description
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.
- Provides ideas for improving the business performance of one’s company or business functions
- Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies
- Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- About the Author
- Foreword
- Acknowledgments
- Introduction
-
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
-
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)
- Chapter 6. Leveraging BI for Performance Management, Process Improvement, and Decision Support
- Chapter 7. Meeting the Challenges of Enterprise BI
- Chapter 8. General Management Perspectives on Technical Topics
- Bibliography
- Index
Product information
- Title: Business Intelligence Strategy and Big Data Analytics
- Author(s):
- Release date: April 2016
- Publisher(s): Morgan Kaufmann
- ISBN: 9780128094891
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