Stephen E. Arnold: In the Cloud Big Data Meta Data Hack

Advanced Cyber/IO, Cloud, Data, IO Impotency, IO Mapping, IO Sense-Making
Stephen E. Arnold
Stephen E. Arnold

Finally Some Cloudy News on Metadata

For Obama’s 2012 re-election campaign, his team broke down data silos and moved all the data to a cloud repository. The team built Narwhal, a shared data store interface for all of the campaigns’ application. Narwhal was dubbed “Obama’s White Whale,” because it is almost a mythical technology that federal agencies have been trying to develop for years. While Obama may be hanging out with Queequag and Ishmael, there is a more viable solution for the cloud says GCN’s article, “Big Metadata: 7 Ways To Leverage Your Data In the Cloud.”

Data silo migration may appear to be a daunting task, but it is not impossible to do. The article states:

“Fortunately, migrating agency data to the cloud offers IT managers another opportunity to break down those silos, integrate their data and develop a unified data layer for all applications. In this article, I want to examine how to design metadata in the cloud to enable the description, discovery and reuse of data assets in the cloud. Here are the basic metadata description methods (what I like to think of as the “Magnificent Seven” of metadata!) and how to apply them to data in the cloud.”

The list runs down seven considerations when moving to the cloud: identification, static and dynamic measurement, degree scales, categorization, relationships, and commentary. The only thing that stands in trashing data silos is security and privacy. While this list is useful it is pretty basic textbook information that is applied to metadata in any situation. What makes it so special for the cloud?

Whitney Grace, December 26, 2013

Sponsored by, developer of Augmentext

Phi Beta Iota: Making sense demands a mix of absolute integrity, a holistic analytic model that demands data gaps be filled, an appreciation for true cost economics, and affordable information technology to enable all stakeholders to play. In short, big data is big garbage without the whole package.

See Also:

Analytics @ Phi Beta Iota

Big Data @ Phi Beta Iota

Open Source @ Phi Beta Iota

True Cost @ Phi Beta Iota



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