Business Intelligence
The Savvy Manager's Guide
- 2nd Edition - October 17, 2012
- Imprint: Morgan Kaufmann
- Author: David Loshin
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 3 8 5 8 8 9 - 4
- eBook ISBN:9 7 8 - 0 - 1 2 - 3 8 5 8 9 0 - 0
Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks… Read more
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Request a sales quoteBusiness Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge.
Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered.
This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts.
- Guides managers through developing, administering, or simply understanding business intelligence technology
- Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization’s data into actionable knowledge
- Contains a handy, quick-reference to technologies and terminology
IT managers, analysts, consultants, MIS students, data managers
Preface
Introduction
What This Book Is
Why You Should Be Reading This Book
Organization of the Book
Our Approach to Knowledge Transfer
Contact Me
Acknowledgements
Foreword
Chapter 1. Business Intelligence and Information Exploitation
Improving the Decision-Making Process
Why a Business Intelligence Program?
Taking Advantage of the Information Asset
Business Intelligence and Program Success
Business Intelligence Defined
Actionable Intelligence
The Analytics Spectrum
Taming the Information Explosion
Considerations
Continuing Your Business Intelligence Education
Endnotes
Chapter 2. The Value of Business Intelligence
Value Drivers and Information Use
Performance Metrics and Key Performance Indicators
Using Actionable Knowledge
Horizontal Use Cases for Business Intelligence
Vertical Use Cases for Business Intelligence
Business Intelligence Adds Value
Chapter 3. Planning for Success
Introduction
Organizational Preparedness for Business Intelligence and Analytics
Initial Steps in Starting a Business Intelligence Program
Bridging the Gaps Between Information Technology and the Business Users
Knowing the Different Types of Business Intelligence Users
Business Intelligence Success Factors: A Deeper Dive
More on Building Your Team
Strategic Versus Tactical Planning
Summary
Endnotes
Chapter 4. Developing Your Business Intelligence Roadmap
A Business Intelligence Strategy: Vision to Blueprint
Review: The Business Intelligence and Analytics Spectrum
The Business Intelligence Roadmap: Example Phasing
Planning the Business Intelligence Plan
Chapter 5. The Business Intelligence Environment
Aspects of a Business Intelligence and Analytics Platform and Strategy
The Organizational Business Intelligence Framework
Services and System Evolution
Management Issues
Additional Considerations
Chapter 6. Business Processes and Information Flow
Analytical Information Needs and Information Flows
Information Processing and Information Flow
The Information Flow Model
Practical Use
Modeling Frameworks
Management Issues
Deeper Dives
Chapter 7. Data Requirements Analysis
Introduction
Business Uses of Information
Metrics: Facts, Qualifiers, and Models
What is Data Requirements Analysis?
Assessing Suitability
Summary
Chapter 8. Data Warehouses and the Technical Business Intelligence Architecture
Introduction
Data Modeling and Analytics
The Data Warehouse
Analytical Platforms
Operational Data Stores
Management
Do You Really Need a Data Warehouse?
Summary
Chapter 9. Metadata
What is Metadata?
The Origin and Utility of Metadata
Types of Metadata
Semantic Metadata Processes for Business Analytics
Further Considerations
Using Metadata Tools
Chapter 10. Data Profiling
Establishing Usability of Candidate Data Sources
Data Profiling Activities
Data Model Inference
Attribute Analysis
Relationship Analysis
Management Issues
Summary
Chapter 11. Business Rules
The Value Proposition of Business Rules
The Business Rules Approach
The Definition of a Business Rule
Business Rule Systems
Sources of Business Rules
Management Issues
To Learn More
Endnotes
Chapter 12. Data Quality
Good Decisions Rely on Quality Information
The Virtuous Cycle of Data Quality
Types of Data Flaws
Business Impacts of Data Flaws
Dimensions of Data Quality
Data Quality Assessment
Data Quality Rules
Continuous Data Quality Monitoring and Improvement
Considerations Regarding Data Quality for Business Analytics
Data Cleansing
Summary
Chapter 13. Data Integration
Improving Data Accessibility
Extraction/Transformation/Loading
Data Latency and Data Synchrony
Data Replication and Change Data Capture
Data Federation and Virtualization
Data Integration and Cloud Computing
Information Protection
More on Merge/Purge and Record Consolidation
Thoughts on Data Stewardship and Governance for Integration
Chapter 14. High-Performance Business Intelligence
The Need for Speed
The Value of Parallelism
Parallel Processing Systems
Symmetric Multiprocessing
Parallelism and Business Intelligence
Performance Platforms and Analytical Appliances
Data Layouts and Performance
MapReduce and Hadoop
Assessing Architectural Suitability for Application Performance
Endnote
Chapter 15. Deriving Insight from Collections of Data
Introduction
Customer Profiles and Customer Behavior
Customer Lifetime Value
Demographics, Psychographics, Geographics
Geographic Data
Behavior Analysis
Consideration When Drawing Inferences
Chapter 16. Creating Business Value through Location-Based Intelligence
The Business Value of Location
Demystifying Geography: Address Versus Location
Geocoding and Geographic Enhancement
Fundamentals of Location-Based Intelligence for Operational Uses
Geographic Data Services
Challenges and Considerations
Where to Next?
Chapter 17. Knowledge Discovery and Data Mining for Predictive Analytics
Business Drivers
Data Mining, Data Warehousing, Big Data
The Virtuous Cycle
Directed Versus Undirected Knowledge Discovery
Six Basic Data Mining Activities
Data Mining Techniques
Technology Expectations
Summary
Chapter 18. Repurposing Publicly Available Data
Using Publicly Available Data: Some Challenges
Public Data
Data Resources
The Myth of Privacy
Information Protection and Privacy Concerns
Finding and Using Open Data Sets
Chapter 19. Knowledge Delivery
Review: The Business Intelligence User Types
Standard Reports
Interactive Analysis and Ad Hoc Querying
Parameterized Reports and Self-Service Reporting
Dimensional Analysis
Alerts/Notifications
Visualization: Charts, Graphs, Widgets
Scorecards and Dashboards
Geographic Visualization
Integrated Analytics
Considerations: Optimizing the Presentation for the Right Message
Chapter 20. Emerging Business Intelligence Trends
Search as a Business Intelligence Technique
Text Analysis
Entity Recognition and Entity Extraction
Sentiment Analysis
Mobile Business Intelligence
Event Stream Processing
Embedded Predictive Analytic Models
Big Data Analytics
Considerations
Endnote
Chapter 21. Quick Reference Guide
Analytics Appliance
Business Analytics
Business Intelligence
Business Rules
Dashboards and Scorecards
Data Cleansing
Data Enhancement
Data Governance
Data Integration
Data Mart
Data Mining
Data Modeling
Data Profiling
Data Quality
Data Warehouse
Dimensional Modeling
ELT (Extract, Load, Transform)
ETL (Extract, Transform, Load)
Event Stream Processing
Hadoop and MapReduce
Location Intelligence and Geographic Analytics
Metadata and Metadata Management
Mobile Business Intelligence
Online Analytical Processing (OLAP)
Parallel and Distributed Computing
Query and Reporting
Endnotes
Bibliography
Index
- Edition: 2
- Published: October 17, 2012
- Imprint: Morgan Kaufmann
- No. of pages: 400
- Language: English
- Paperback ISBN: 9780123858894
- eBook ISBN: 9780123858900
DL
David Loshin
David Loshin is President of Knowledge Integrity, Inc., a company specializing in data management consulting. The author of numerous books on performance computing and data management, including “Master Data Management" (2008) and “Business Intelligence – The Savvy Manager’s Guide" (2003), and creator of courses and tutorials on all facets of data management best practices, David is often looked to for thought leadership in the information management industry.
Affiliations and expertise
President, Knowledge Integrity Incorporated, Silver Spring, MD, USARead Business Intelligence on ScienceDirect