Business intelligence guidebook from data integration to analytics
This book arms you with the knowledge you need to design rock-solid business intelligence and data integration processes. Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-make...
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| Format: | eBook |
| Language: | English |
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Waltham, MA
Morgan Kaufman
2015
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| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Includes bibliographical references and index
- Where are the Product and Vendor Names?
- Evolution Not Revolution
- Technology Architecture
- Product and Technology Evaluations
- Part IV. Data Design
- Chapter 8. Foundational Data Modeling
- The Purpose of Data Modeling
- Definitions-The Difference Between a Data Model and Data Modeling
- Three Levels of Data Models
- Data Modeling Workflow
- Where Data Models Are Used
- Entity-Relationship (ER) Modeling Overview
- Normalization
- Limits and Purpose of Normalization
- Chapter 9. Dimensional Modeling
- Introduction to Dimensional Modeling
- High-Level View of a Dimensional Model
- Facts
- Dimensions
- Schemas
- Entity Relationship versus Dimensional Modeling
- Purpose of Dimensional Modeling
- Fact Tables
- Achieving Consistency
- Advanced Dimensions and Facts
- Dimensional Modeling Recap
- Chapter 10. Business Intelligence Dimensional Modeling
- Introduction
- Hierarchies
- Outrigger Tables
- Slowly Changing Dimensions
- Causal Dimension
- Multivalued Dimensions
- Junk Dimensions
- Value Band Reporting
- Heterogeneous Products
- Alternate Dimensions
- Too Few or Too Many Dimensions
- Part V. Data Integration Design
- Chapter 11. Data Integration Design and Development
- Getting Started with Data Integration
- Data Integration Architecture
- Data Integration Requirements
- Data Integration Design
- Data Integration Standards
- Loading Historical Data
- Data Integration Prototyping
- Data Integration Testing
- Chapter 12. Data Integration Processes
- Introduction: Manual Coding versus Tool-Based Data Integration
- Data Integration Services
- Part VI. Business Intelligence Design
- Chapter 13. Business Intelligence Applications
- Revise BI Applications List
- BI Personas
- BI Design Layout-Best Practices
- Data Design for Self-Service BI
- Matching Types of Analysis to Visualizations
- Intro
- Cover image
- Title page
- Table of Contents
- Copyright
- Foreword
- How to Use This Book
- Acknowledgments
- Part I. Concepts and Context
- Chapter 1. The Business Demand for Data, Information, and Analytics
- Just One Word: Data
- Welcome to the Data Deluge
- Taming the Analytics Deluge
- Too Much Data, Too Little Information
- Data Capture versus Information Analysis
- The Five Cs of Data
- Common Terminology from our Perspective
- Part II. Business and Technical Needs
- Chapter 2. Justifying BI: Building the Business and Technical Case
- Why Justification is Needed
- Building the Business Case
- Building the Technical Case
- Assessing Readiness
- Creating a BI Road Map
- Developing Scope, Preliminary Plan, and Budget
- Obtaining Approval
- Common Justification Pitfalls
- Chapter 3. Defining Requirements-Business, Data and Quality
- The Purpose of Defining Requirements
- Goals
- Deliverables
- Roles
- Defining Requirements Workflow
- Interviewing
- Documenting Requirements
- Part III. Architectural Framework
- Chapter 4. Architecture Framework
- The Need for Architectural Blueprints
- Architectural Framework
- Information Architecture
- Data Architecture
- Technical Architecture
- Product Architecture
- Metadata
- Security and Privacy
- Avoiding Accidents with Architectural Planning
- Do Not Obsess over the Architecture
- Chapter 5. Information Architecture
- The Purpose of an Information Architecture
- Data Integration Framework
- DIF Information Architecture
- Operational BI versus Analytical BI
- Master Data Management
- Chapter 6. Data Architecture
- The Purpose of a Data Architecture
- History
- Data Architectural Choices
- Data Integration Workflow
- Data Workflow-Rise of EDW Again
- Operational Data Store
- Chapter 7. Technology & Product Architectures
- BI Content Specifications
- Chapter 14. BI Design and Development
- BI Design
- BI Development
- BI Application Testing
- Chapter 15. Advanced Analytics
- Advanced Analytics Overview and Background
- Predictive Analytics and Data Mining
- Analytical Sandboxes and Hubs
- Big Data Analytics
- Data Visualization
- Chapter 16. Data Shadow Systems
- The Data Shadow Problem
- Are There Data Shadow Systems in Your Organization?
- What Kind of Data Shadow Systems Do You Have?
- Data Shadow System Triage
- The Evolution of Data Shadow Systems in an Organization
- Damages Caused by Data Shadow Systems
- The Benefits of Data Shadow Systems
- Moving beyond Data Shadow Systems
- Misguided Attempts to Replace Data Shadow Systems
- Renovating Data Shadow Systems
- Part VII. Organization
- Chapter 17. People, Process and Politics
- The Technology Trap
- The Business and IT Relationship
- Roles and Responsibilities
- Building the BI Team
- Training
- Data Governance
- Chapter 18. Project Management
- The Role of Project Management
- Establishing a BI Program
- BI Assessment
- Work Breakdown Structure
- BI Architectural Plan
- BI Projects Are Different
- Project Methodologies
- BI Project Phases
- BI Project Schedule
- Chapter 19. Centers of Excellence
- The Purpose of Centers of Excellence
- BI COE
- Data Integration Center of Excellence
- Enabling a Data-Driven Enterprise
- Index