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Disparate data sources that can help identify risks around sales practice should be unified in order to provide a complete 360 degree view of customers' accounts, services, communications, and employee interactions.
Working with such disparate data sources presents challenges, however.
Our analysis draws upon disparate data sources to compile projections.
In maintenance, the problem of disparate data sources is important.
Taking disparate data sources and giving them a unified view is tricky: do the data sets match?
The challenge for these methods was finding ways to integrate disparate data sources and properly handle incomplete and noisy data.
Open innovation holds that it is quite possible to aggregate disparate data sources from multiple, collaborating organizations.
The disparate data sources are often called "silos," suggesting the challenge of mingling different data sets to generate insights.
"The huge thing is the ability to connect disparate data sources," said Mike Bergman, a computer scientist and consultant who is credited with coining the term Deep Web.
We find that a systems biology approach that combines genome-scale experimentation and computation can systematically generate hypotheses on the basis of disparate data sources.
The task of probabilistic record linkage is to find and link records that refer to the same entity across several disparate data sources.
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