Duration:

Two day classroom instruction.

Onsite training has the option of:

  • Two day classroom instruction, or
  • Three day classroom instruction and workshop

Prerequisite Education or Experience

Concepts and Fundamentals for Data Warehousing & Business Intelligence or equivalent knowledge or experience.

Course Outline:

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


  • Workshop Session (below)

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?


  • Workshop Session (below)


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


  • Workshop Session (below)

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


Workshop Sessions:

If three day classroom and workshop option is selected.

Workshops occur after sections 2, 3 & 4 to put in your company’s context

  • Assess Your Current Situation
  • Examine Factors Impacting Decisions
  • Review Architectural Options In Your Context
    • Strengths And Weaknesses
    • Resource, Timing And Cost Considerations


  • Preliminary recommendations for your organization