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230202 ||| eng |
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4 |
|a Q336
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1 |
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|a Davenport, Thomas H.
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| 245 |
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|a How AI is improving data management
|b aritificial intelligence is quietly improving the management of data, including its quality, accessibility, and security
|c Thomas H. Davenport and Thomas C. Redman
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| 246 |
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1 |
|a How artificial intelligence is improving data management
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| 250 |
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|a [First edition]
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| 260 |
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|a [Cambridge, Massachusetts]
|b MIT Sloan Management Review
|c 2022
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| 300 |
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|a 7 pages
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| 653 |
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|a Big data / fast
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| 653 |
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|a Artificial intelligence / Data processing / http://id.loc.gov/authorities/subjects/sh85008182
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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 Données volumineuses
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| 653 |
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|a Artificial intelligence / Data processing / fast
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| 653 |
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|a Intelligence artificielle / Informatique
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| 700 |
1 |
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|a Redman, Thomas C.
|e author
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
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|a "Reprint 64309."
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| 856 |
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|u https://learning.oreilly.com/library/view/~/53863MIT64309/?ar
|x Verlag
|3 Volltext
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|a 006.3
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| 520 |
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|a Artificial intelligence has been applied successfully in thousands of ways, but one of the less visible and less dramatic ones is improving data management. The authors describe five common areas of data management -- classifying, cataloging, quality, security, and data integration -- where they see AI playing important roles. They also discuss the vendor landscape and the ways that humans are essential to data management
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