000 | 03554naaaa2200529uu 4500 | ||
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003 | BUT | ||
005 | 20230512120922.0 | ||
006 | m o d | ||
007 | cr|mn|---annan | ||
008 | 20220514s2022 xx |||||o ||| Eng|| d | ||
020 | _a9783030783075 | ||
040 |
_aoapen _coapen |
||
041 | 0 | _aeng | |
080 | _a004 | ||
100 | 1 |
_aCurry, Edward _4edt |
|
245 | 1 | 0 | _aTechnologies and Applications for Big Data Value |
260 |
_aCham _bSpringer Nature _c2022 |
||
300 | _a1 electronic resource (544 p.) | ||
506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
520 | _aThis open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems. | ||
540 |
_aCreative Commons _fby/4.0/ _2cc |
||
546 | _aEnglish | ||
650 | 0 |
_aИскусственный интеллект _2bicssc _94518 |
|
650 | 0 |
_aБазы данных _92229 |
|
653 | _aBig Data | ||
653 | _aData Management | ||
653 | _aData Processing | ||
653 | _aData Analytics | ||
653 | _aData Visualisation and User Interaction | ||
653 | _aKnowledge Discovery | ||
653 | _aInformation Retrieval | ||
700 | 1 |
_aAuer, Sören _4edt |
|
700 | 1 |
_aBerre, Arne J. _4edt |
|
700 | 1 |
_aMetzger, Andreas _4edt |
|
700 | 1 |
_aPerez, Maria S. _4edt |
|
700 | 1 |
_aZillner, Sonja _4edt |
|
700 | 1 |
_aCurry, Edward _4oth |
|
700 | 1 |
_aAuer, Sören _4oth |
|
700 | 1 |
_aBerre, Arne J. _4oth |
|
700 | 1 |
_aMetzger, Andreas _4oth |
|
700 | 1 |
_aPerez, Maria S. _4oth |
|
700 | 1 |
_aZillner, Sonja _4oth |
|
856 | 4 | 0 |
_awww.oapen.org _uhttps://library.oapen.org/bitstream/20.500.12657/54415/1/978-3-030-78307-5.pdf _70 _zDownload |
856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/81694 _70 _zDescription |
909 |
_c4 _dDarya Shvetsova |
||
942 |
_2udc _cEE |
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999 |
_c6556 _d6556 |