Data federation is run-time technology that makes it easy for an application to access a heterogeneous set of data stores. In this case, the data federator deals with all the different API's, the different database languages, it will try to optimize access to those data stores by doing distributed join optimization, and it will handle all the issues of distributed transactions.
In my book on data virtualization (Data Virtualization for Business Intelligence Systems), I define data federation as follows:
Data federation is an aspect of data virtualization where the data stored in a heterogeneous set of autonomous data stores is made accessible to data consumers as one integrated data store by using on-demand data integration.
Data virtualization is much more than data federation. Here are some of the features supported by data virtualization servers today:
- Self-service, iterative, and collaborative development
- (Canonical) data modeling
- On-demand data profiling and data cleansing
- Full support for the entire development life cycle: business glossary, information modeling
- Extensive data integrity features
- Extensive master data management features
- Integration of different data integration styles, including ETL, ELT, and replication
If you want to know more about this topic, attend my session at the The Data Virtualization Experts Forum.
Posted September 21, 2012 1:41 AM
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