Off late, I was posed with a question by my colleague
during a brain-storming session:
Are Data Virtualization and Data
Federation different?
Aren’t they synonymous?
This put me on a search if there are any good definitions around already for
these that would not only verify my understanding, also enables me in future
for easier demonstrations. Bang on! I
could find one of the definitions by Rick van der Lans that I would
like to agree with. Rick’s proposed
definitions are:
Data Virtualization:
Data virtualization is
the process of offering data consumers a data access interface that hides the
technical aspects of stored data, such as location, storage structure, API,
access language, and storage technology.
Data Federation:
Data federation is a
form 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.
Though the terms data virtualization and data federation are
still used interchangeably in current world and standards definitions are yet
to be accepted widely.
Recently we were looking for a tool that
can act as a work horse for virtual data warehouse implementation. Sounds
simple but needs a deep dive before taking this architectural decision. Few
scenarios in which we chose Virtual Data Warehouse as one of the viable solution that could ensure successful delivery and add value are:
- As a strategic solution to showcase the benefits of data integration and Data Mart/Data warehouse implementation
- As a mid-term solution where the data volumes and complexity is not a concern
- As a strategic solution to showcase the registry model implementation of a master data management solution
There are few other scenarios which are identified for evaluation and progress so far looks promising. Will continue writing on this post with the tools we considered and so on.
Looking forward to hear back your experiences in this area.
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