ODI11G:Data Integration

1. Integrating data and applications throughout the enterprise, and presenting them in a unified view is a complex proposition.
2.  Not only are there broad disparities in technologies, data structures, and application functionality, but there are also fundamental differences in integration architectures. 
3. Some integration needs are Data Oriented, especially those involving large data volumes.
4. Other integration projects lend themselves to an Event Driven Architecture (EDA) or a Service Oriented Architecture (SOA), for asynchronous or synchronous integration.
5. Data Integration ensures that information is timely, accurate, and consistent across complex systems. 
6. Although it is still frequently referred as Extract-Load-Transform (ETL) - Data Integration was initially considered as the architecture used for loading Enterprise Data Warehouse systems - data integration now includes data movement, data synchronization, data quality, data management, and data services.