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