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Titlebook: Big Data Imperatives; Enterprise Big Data Soumendra Mohanty,Madhu Jagadeesh,Harsha Srivatsa Book 2013 Soumendra Mohanty and Madhu Jagadees

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11#
發(fā)表于 2025-3-23 12:07:00 | 只看該作者
https://doi.org/10.1007/978-1-4613-3387-6se wide programs or through business functions or IT), the typical volumes of data were in the range of few terabytes and in some cases due to compliance and regulation requirements the volumes expectedly went up several notches higher.
12#
發(fā)表于 2025-3-23 16:56:31 | 只看該作者
,“Big Data” in the Enterprise,se wide programs or through business functions or IT), the typical volumes of data were in the range of few terabytes and in some cases due to compliance and regulation requirements the volumes expectedly went up several notches higher.
13#
發(fā)表于 2025-3-23 18:43:12 | 只看該作者
Book 2013nections between data elements that must be probabilistically inferred .Big Data Imperatives.?explains ‘what big data can do‘. It can batch process millions and billions of records both unstructured and structured much faster and cheaper. Big data analytics provide a platform to merge all analysis w
14#
發(fā)表于 2025-3-23 23:53:41 | 只看該作者
15#
發(fā)表于 2025-3-24 02:40:03 | 只看該作者
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發(fā)表于 2025-3-24 07:22:05 | 只看該作者
17#
發(fā)表于 2025-3-24 14:35:46 | 只看該作者
Extracting Value From Big Data: In-Memory Solutions, Real Time Analytics, And Recommendation System.
18#
發(fā)表于 2025-3-24 16:35:34 | 只看該作者
,“Big Data” in the Enterprise,ent of mainframes to client server to ERP and now everything digital. For years the overwhelming amount of data produced was deemed useless. But data has always been an integral part of every enterprise, big or small. As the importance and value of data to an enterprise became evident, so did the pr
19#
發(fā)表于 2025-3-24 22:22:42 | 只看該作者
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發(fā)表于 2025-3-25 01:42:34 | 只看該作者
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