Book description
Business 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
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Preface
- 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
-
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
- Chapter 5. The Business Intelligence Environment
- Chapter 6. Business Processes and Information Flow
- Chapter 7. Data Requirements Analysis
- Chapter 8. Data Warehouses and the Technical Business Intelligence Architecture
- Chapter 9. Metadata
- Chapter 10. Data Profiling
- Chapter 11. Business Rules
-
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
- Chapter 16. Creating Business Value through Location-Based Intelligence
- Chapter 17. Knowledge Discovery and Data Mining for Predictive Analytics
- Chapter 18. Repurposing Publicly Available Data
-
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
-
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
Product information
- Title: Business Intelligence, 2nd Edition
- Author(s):
- Release date: November 2012
- Publisher(s): Morgan Kaufmann
- ISBN: 9780123858900
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