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The need for intelligent tools to bridge this gap, to rescue the knowledge being systematically isolated in literature and data silos, is now widely acknowledged.
Despite a number of conventional data mining techniques and methods, these classical approaches are restricted to isolated or "silo" data sets and therefore remain primarily stand alone and specialized in nature.
Data silos themselves are not the problem.
Data is king, and business processes became embedded in data silos.
Gary Markham: In data management, and spend management specifically, data silos have been a significant issue.
In data management, and spend management specifically, data silos have been a significant issue.
Most often, data resides in disparate databases, data silos and/or applications.
We do want to bust open those data silos.
However, eliminating data silos allows you to share data across departments to offer richer data access to everyone.
Which again is one of the commercial reasons why big data silos often stay just that: Silos.
Unfortunately, data silos and outdated practices have made it difficult to unlock opportunities.
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