|
|
|
|
| LEADER |
03218nmm a2200421 u 4500 |
| 001 |
EB001911286 |
| 003 |
EBX01000000000000001074188 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
210123 ||| eng |
| 050 |
|
4 |
|a QA76.9.B45
|
| 245 |
0 |
0 |
|a Big data now
|b 2014 edition : current perspectives from O'Reilly Media
|
| 250 |
|
|
|a First edition
|
| 260 |
|
|
|a Sebastopol, CA
|b O'Reilly Media
|c 2015
|
| 300 |
|
|
|a 1 volume
|b illustrations
|
| 505 |
0 |
|
|a Includes bibliographical references
|
| 653 |
|
|
|a Data mining / fast
|
| 653 |
|
|
|a Technologie de l'information / Gestion
|
| 653 |
|
|
|a Big data / fast
|
| 653 |
|
|
|a Information technology / Management / fast
|
| 653 |
|
|
|a Big data / http://id.loc.gov/authorities/subjects/sh2012003227
|
| 653 |
|
|
|a Artificial intelligence / fast
|
| 653 |
|
|
|a Artificial intelligence / http://id.loc.gov/authorities/subjects/sh85008180
|
| 653 |
|
|
|a Données volumineuses
|
| 653 |
|
|
|a Intelligence artificielle
|
| 653 |
|
|
|a artificial intelligence / aat
|
| 653 |
|
|
|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
|
| 653 |
|
|
|a Information technology / Management / http://id.loc.gov/authorities/subjects/sh2008006980
|
| 653 |
|
|
|a Exploration de données (Informatique)
|
| 710 |
2 |
|
|a O'Reilly & Associates
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b OREILLY
|a O'Reilly
|
| 500 |
|
|
|a "The topics in this 2014 edition of Big Data Now represent the major forces currently shaping the data world"--Resource description page
|
| 776 |
|
|
|z 9781491917367
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9781492048091/?ar
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 658
|
| 082 |
0 |
|
|a 000
|
| 520 |
|
|
|a In the four years that O'Reilly has produced its annual Big Data Now report, the data field has grown from infancy into young adulthood. Data is now a leader in some fields and a driver of innovation in others, and companies that use data and analytics to drive decision-making are outperforming their peers. And while access to big data tools and techniques once required significant expertise, today many tools have improved and communities have formed to share best practices. Companies have also started to emphasize the importance of processes, culture, and people. The topics in this 2014 edition of Big Data Now represent the major forces currently shaping the data world: Cognitive augmentation: predictive APIs, graph analytics, and Network Science dashboards Intelligence matters: defining AI, modeling intelligence, deep learning, and "summoning the demon" Cheap sensors, fast networks, and distributed computing: stream processing, hardware data flows, and computing at the edge Data (science) pipelines: broadening the coverage of analytic pipelines with specialized tools Evolving marketplace of big data components: SSDs, Hadoop 2, Spark; and why datacenters need operating systems Design and social science: human-centered design, wearables and real-time communications, and wearable etiquette Building a data culture: moving from prediction to real-time adaptation; and why you need to become a data skeptic Perils of big data: data redlining, intrusive data analysis, and the state of big data ethics
|