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Analyzing large datasets in the cloud is different from performing the same analysis in a local environment.
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It is not trivial to move large datasets around in the cloud.
The scheme presented in this paper does not consider dataset partitioning in the cloud because user's rating data are not stored in the cloud at all.
Second, we now have the ability to digitize massive data into unstructured datasets, often stored in the cloud.
Why go through the hassle of trying to move massive datasets to compute in the cloud when you can bring compute to the data and run your app there?
It automates tiering of petabyte-scale datasets to object stores in the cloud or on the premises.
We extracted some versions from randomly chosen links to common datasets in the linked open data (LOD) cloud [22], such as Dbpedia and DBPL, as well as FOAF Profiles.
A spatiotemporal technique for data compression on big graph data in the cloud generates reduced datasets [45].
In many companies, analytics is no longer a manual process based on static datasets; instead, it is completely embedded in code and in the cloud, integrated with the rest of the organization's processes.
First: iTunes in the cloud.
Prepare for a dogfight in the cloud.
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