標(biāo)題: Titlebook: Big Data Imperatives; Enterprise Big Data Soumendra Mohanty,Madhu Jagadeesh,Harsha Srivatsa Book 2013 Soumendra Mohanty and Madhu Jagadees [打印本頁] 作者: 評估 時(shí)間: 2025-3-21 18:33
書目名稱Big Data Imperatives影響因子(影響力)
書目名稱Big Data Imperatives影響因子(影響力)學(xué)科排名
書目名稱Big Data Imperatives網(wǎng)絡(luò)公開度
書目名稱Big Data Imperatives網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Big Data Imperatives被引頻次
書目名稱Big Data Imperatives被引頻次學(xué)科排名
書目名稱Big Data Imperatives年度引用
書目名稱Big Data Imperatives年度引用學(xué)科排名
書目名稱Big Data Imperatives讀者反饋
書目名稱Big Data Imperatives讀者反饋學(xué)科排名
作者: countenance 時(shí)間: 2025-3-21 23:43 作者: 預(yù)知 時(shí)間: 2025-3-22 03:56 作者: 著名 時(shí)間: 2025-3-22 05:43 作者: 珍奇 時(shí)間: 2025-3-22 09:12
J. C. E. Underwood MD, MRCPath.Big data is baffling, and analytics are complex. Together, big data analytics make a difficult and complex undertaking largely because technology architectures and methodologies are immature.作者: paltry 時(shí)間: 2025-3-22 15:41 作者: investigate 時(shí)間: 2025-3-22 20:52 作者: Dorsal-Kyphosis 時(shí)間: 2025-3-22 21:16
https://doi.org/10.1007/978-1-4613-3387-6ent 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作者: 交響樂 時(shí)間: 2025-3-23 02:51
etc;.Numerous industry use cases about big data and its impl.Big Data Imperatives., focuses on resolving the key questions on everyone’s mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it 作者: 不適當(dāng) 時(shí)間: 2025-3-23 08:28 作者: 北極熊 時(shí)間: 2025-3-23 12:07
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.作者: lacrimal-gland 時(shí)間: 2025-3-23 16:56
,“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.作者: Mortal 時(shí)間: 2025-3-23 18:43
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作者: pus840 時(shí)間: 2025-3-23 23:53 作者: 慷慨不好 時(shí)間: 2025-3-24 02:40 作者: Malcontent 時(shí)間: 2025-3-24 07:22 作者: 膠狀 時(shí)間: 2025-3-24 14:35
Extracting Value From Big Data: In-Memory Solutions, Real Time Analytics, And Recommendation System.作者: 招惹 時(shí)間: 2025-3-24 16:35
,“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作者: 試驗(yàn) 時(shí)間: 2025-3-24 22:22
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