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Today’s business managers depend heavily on data analysis and decision-speed information, raising the stakes for data integration. At the same time, the work of integrating data has become increasingly complex. The simple processes of extract, transform, and load (ETL) integration for structured enterprise data no longer meet the need. Unstructured data, big data, departmental data, end-user data, and external data all challenge old models for data integration. Meeting modern data integration challenges calls for data integration strategy and architecture.
Get ready to build reliable and adaptable data integration systems and to make the most of recent advances in data integration technologies by following the path of strategy first, architecture next, and then integration systems and technology.
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?
Data Integration Strategy Defined
Elements of Data Integration Strategy
Data Consumers and Data Sources
Data Integration Processes
Access and Navigation
The Big Picture
Creating Data Integration Strategy
Goals and States
Applied Data Integration Strategy
Planning and Projects
Module 2 - Data Integration Architecture
What Is Data Integration Architecture?
Data Integration Architecture Defined
Methods of Information Sharing
Shared Databases and Replication
Gateways and Portals
Data Services & Messaging
Publish and Subscribe, File Transfer
Virtualization and Federation
Architecture Concepts and Components
Constructs in Data Integration Architecture
Module 3 - Creating Data Integration Architecture
Source Data Locations and Technologies
TDWI Data Integration Principles and Practices: Creating Information Unity from
Data Integration Functions
Data Integration Methods
Architecture Design and Definition
Define the End Points
Structure the Middle
Define Data Access
Data Integration Approaches
Many Types and Levels of Integration
Big Data Integration
Module 4 - Using Data Integration Architecture
Systems and Data Integration Architecture
Development and Data Integration Architecture
Design and Construction
Management and Data Integration Architecture
Management and Governance
Support and Operations
What Will You Do Next?