TDWI Data Integration Principles and Practices: Creating Information Unity from Data Disparity Training

BI, MDM, and data warehousing program and project managers; data integration architects, designers, and developers; data and technology architects.

• The role, purpose, and issues of data integration strategy
• How to fit unstructured data into integration strategy, architecture, and systems
• How to use integration architecture and patterns to handle large volume data challenges
• How to apply architecture and patterns for enterprise, departmental, and local data
• How to select, mix-and-match, and apply several data integration methods including ETL, federated, service-oriented, and virtualized
• Techniques to collect and manage data integration requirements
• Tips and techniques for success throughout the data integration lifecycle—strategy, architecture, systems development, and operations

Module 1 - Data Integration Strategy

• What Is Data Integration Strategy?
  • Strategy Defined
  • Data Integration Strategy Defined
• Elements of Data Integration Strategy
  • Data Consumers and Data Sources
  • Data Integration Processes
  • Data Stores 
  • Access and Navigation
  • Control Objectives
  • The Big Picture
• Creating Data Integration Strategy
  • Goals and States
  • Analysis
• Applied Data Integration Strategy
  • Planning and Projects
  • Data Governance

Module 2 - Data Integration Architecture

• What Is Data Integration Architecture?
  • Architecture Defined
  • Data Integration Architecture Defined
• Integration Patterns
  • Methods of Information Sharing
  • Shared Databases and Replication
  • Gateways and Portals
  • Entity Aggregation
  • Data Services
  • Data Services & Messaging
  • Publish and Subscribe, File Transfer
  • Virtualization
  • Virtualization and Federation
• Architecture Concepts and Components
  • Constructs in Data Integration Architecture
  • Reference Architecture

Module 3 - Creating Data Integration Architecture

• Data Sources
  • Source Systems
  • Structural Variations
  • Source Data Locations and Technologies
• Data Flow
  • Data Acquisition
  • TDWI Data Integration Principles and Practices: Creating Information Unity from
  • Data Disparity
  • Data Integration Functions
  • Data Stores
  • Data Integration Methods
  • Data Delivery
  • Metadata Flow
• Data Consumers
  • People
  • Applications
  • Requirements
• Architecture Design and Definition
  • Define the End Points
  • Structure the Middle
  • Define Data Access
  • Architecture Validation
• Data Integration Approaches
  • Many Types and Levels of Integration
  • ETL/ELT
  • Streaming
  • o Virtualization
  • Federation
  • Big Data Integration
  • Self-Service Integration
  • Cloud Integration
  • Hybrid Integration

Module 4 - Using Data Integration Architecture

• Systems and Data Integration Architecture
  • Existing Systems
  • New Systems
• Development and Data Integration Architecture
  • Requirements Analysis
  • Design and Construction
  • Testing
• Management and Data Integration Architecture
  • Management and Governance
  • Change Management
  • Support and Operations
• Next Steps
  • What Will You Do Next?