Course Outline: Business Intelligence and Data Warehousing Architecture


Section 0: Introductions
  • Instructor & class introductions
Section 1: The Architectures
  • The Four Architectures
    • Information Architecture
    • Data Architecture
    • Technology Architecture
    • Product Architecture
  • Data Integration Framework (DIF)
    • Architecture
    • Processes & Data Stores
    • Standards
    • Tools
    • Resources & Skills

Section 2: DIF Processes
  • Data Preparation
    • Data Sourcing
    • Data Cleansing
    • Data Quality
    • Data Transformation
    • Data Loading

  • Data Franchising
    • Data filtering
    • Data Summarization & Aggregation
    • Data Transformation
    • Data Loading
  • Information Access & Analytics
    • Information Access & Reporting
    • Analytics & Performance Management

  • Metadata Management
    • Inter-tool interfaces
    • Audit & What-If Capability

  • Data Management
    • Data Modeling
    • Data Profiling
    • Database Management
Section 3: Data Store Components
  • Data Modeling Basics
    • Conceptual, Logical & Physical Models
    • Entity-Relationship & Dimensional Modeling

  • Data Structure Concepts
    • Facts, Dimensions, Reference
    • Types of Keys

  • Data Structure Options
    • Star
    • Snowflake
    • Normalized (3NF)
    • Denormalized
    • Others
    • Why do these structures matter?

  • Metadata
    • Technical
    • Business
    • Process
    • Why does metadata matter?

Section 4: DIF Data Stores
  • DIF Data Stores
    • Data Sources
    • Data Warehouse
    • Data Marts
    • Cubes
    • Data Shadow Systems
    • Operational Data Stores (ODS)
    • Data Staging
    • Best Practices & Best Fit Considerations

  • DIF Architectural Options
    • Data Warehouse vs. Data Mart
    • Stand-alone, Federated & Hub and Spoke
    • “Closed loop”
    • Comparison of Architectural Options
Section 5: DIF Tools & Technology
  • Extract, Transform & Loading (ETL)
  • Enterprise Information Integration (EII)
  • Enterprise Application Integration (EAI)
  • Data Profiling
  • Data Quality & Cleansing
  • Metadata Management
  • What about unstructured data?
  • Searching for information

Section 6: DIF Standards
  • Project management
  • Software development
  • Technology and products
  • Architecture
  • Data
Section 7: Conclusions
  • Highlights
  • References & Resources

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