Business Intelligence, 2nd Edition

The Savvy Manager's Guide

Business Intelligence, 2nd Edition,David Loshin,ISBN9780123858894


Morgan Kaufmann




229 X 152

This completely updated best seller is a must read for anyone who wants an understanding of business intelligence, business management disciplines, data warehousing, and how all of the pieces work together

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Key Features

  • 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


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.


IT managers, analysts, consultants, MIS students, data managers

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, USA

View additional works by David Loshin

Business Intelligence, 2nd Edition



What This Book Is

Why You Should Be Reading This Book

Organization of the Book

Our Approach to Knowledge Transfer

Contact Me



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


Continuing Your Business Intelligence Education


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


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



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


Business Uses of Information

Metrics: Facts, Qualifiers, and Models

What is Data Requirements Analysis?

Assessing Suitability


Chapter 8. Data Warehouses and the Technical Business Intelligence Architecture


Data Modeling and Analytics

The Data Warehouse

Analytical Platforms

Operational Data Stores


Do You Really Need a Data Warehouse?


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


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


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


Chapter 13. Data Integration

Improving Data Accessibility


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


Chapter 15. Deriving Insight from Collections of Data


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


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


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



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




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