This is an overview of the difference between application integration and data integration, the differences in use and requirements for DI between business intelligence and OLTP, some integration architecture discussion, and why open source is an even better fit in the operational DI arena than it is for BI projects.
If you want to download a PDF of the slides or listen to a replay, you can find this talk under "How to Use the Right Tools for Operational Data Integration" on Talend's webcast page. There's no direct link to the presentation page so you have to click through.
Data integration tools were once used solely in support of data warehousing, but that has been changing over the past few years. The fastest growing area today for data integration is outside the data warehouse, whether it's one-time data movement for A MySQL upgrade, application consolidation, or real-time data synchronization for master data management projects.
Data integration tools have proven to be faster, more flexible and more cost effective for operational data integration than the common practice of hand-coding or using application integration technologies. The developer focus of these technologies also makes them a prime target for open source commoditization.
During the presentation you will learn about the differences between analytical and operational data integration, technology patterns and options, and recommendations for how to begin using tools for operational data integration.
- How to map common project scenarios to integration architectures and tools
- The technology and market changes that favor use of tools for operational data integration
- The differing requirements for operational vs. analytic data integration
- Advantages of open source for data integration tasks embed:
Posted March 23, 2009 5:00 AM
Permalink | No Comments |