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210123 ||| eng |
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|a 0429101368
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|a 9781306124249
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| 020 |
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|a 9781466578388
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| 020 |
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|a 1466578386
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|a 9780429101366
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| 050 |
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4 |
|a QA76.9.D3
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| 100 |
1 |
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|a Akerkar, Rajendra
|e editor
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| 245 |
0 |
0 |
|a Big data computing
|c edited by Rajendra Akerkar
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| 260 |
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|a Boca Raton
|b CRC Press, Taylor & Francis Group
|c 2014
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| 300 |
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|a xxii, 537 pages
|b illustrations
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| 505 |
0 |
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|a Includes bibliographical references and index
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| 505 |
0 |
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|a Section 1. Introduction -- section 2. Semantic technologies and big data -- section 3. Big data processing -- section 4. Big data and business -- section 5. Big data applications
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| 653 |
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|a Bases de données / Gestion
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| 653 |
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|a Data Mining
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| 653 |
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|a Big data / fast
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| 653 |
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|a Exploration de données (Informatique)
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| 653 |
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|a Database management / fast
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| 653 |
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|a Database management / http://id.loc.gov/authorities/subjects/sh85035848
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| 653 |
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|a BUSINESS & ECONOMICS / Information Management / bisacsh
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| 653 |
|
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|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
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| 653 |
|
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|a COMPUTERS / Database Management / Data Mining / bisacsh
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| 653 |
|
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|a Big data / http://id.loc.gov/authorities/subjects/sh2012003227
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| 653 |
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|a COMPUTERS / Database Management / General / bisacsh
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| 653 |
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|a Données volumineuses
|
| 653 |
|
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|a COMPUTERS / General / bisacsh
|
| 653 |
|
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|a Data mining / fast
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
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|b OREILLY
|a O'Reilly
|
| 776 |
|
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|z 0429101368
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| 776 |
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|z 9781466578388
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| 776 |
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|z 9781466578371
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| 776 |
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|z 9780429101366
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| 776 |
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|z 1466578378
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| 776 |
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|z 1466578386
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| 856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9781466578388/?ar
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 006.3/12
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| 082 |
0 |
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|a 330
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| 082 |
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|a 658
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| 520 |
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|a "To tackle the challenges of Big Data, novel approaches and tools have emerged. Moreover, the technology required for big-data computing is developing at a satisfactory rate due to market forces and technological evolution. This book presents a mix of theory and industry cases that discuss the technical and practical issues related to Big Data in intelligent information management. It emphasizes the adoption and diffusion of Big Data tools and technologies in real practical applications. In addition, the book balances between academic and industry contributions"--
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