LEADER 03348oam 2200505 450 001 9910741174803321 005 20230824081306.0 010 $a3-319-38992-0 024 7 $a10.1007/978-3-319-38992-9 035 $a(CKB)3710000000717994 035 $a(DE-He213)978-3-319-38992-9 035 $a(MiAaPQ)EBC4532441 035 $a(PPN)194078221 035 $a(EXLCZ)993710000000717994 100 $a20160524d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig data analytics $ea management perspective /$fby Francesco Corea 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 210 4$dİ2016 215 $a1 online resource (XIII, 48 p. 7 illustations in color.) 225 1 $aStudies in Big Data,$x2197-6503 ;$v21 311 0 $a3-319-38991-2 320 $aIncludes bibliographical references at the end of each chapters. 327 $aIntroduction -- What Data Science Means to the Business -- Key Data Challenges to Strategic Business Decisions -- A Chimera Called Data Scientist: Why they don?t Exist (but they will in the Future) -- Future Data Trends -- Where are we Going? The Path Toward an Artificial Intelligence -- Conclusions. 330 $aThis book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership ? while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively. 410 0$aStudies in Big Data,$x2197-6503 ;$v21 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aBig data 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aBig data. 676 $a658.4038011 700 $aCorea$b Francesco$0761218 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910741174803321 996 $aBig Data Analytics$91541087 997 $aUNINA LEADER 01169nam 2200373 450 001 9910828237103321 005 20230629234725.0 010 $a90-04-44033-X 035 $a(CKB)4100000011560393 035 $a(MiAaPQ)EBC6384978 035 $a(EXLCZ)994100000011560393 100 $a20210327d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aChrysomeloidea i (vesperidae, disteniidae, cerambycidae) $eupdated and revised second edition /$fedited by Mikhail Danilevsky 210 1$aLeiden, the Netherlands ;$aBoston, Massachusetts :$cBRILL,$d[2021] 210 4$dİ2021 215 $a1 online resource (740 pages) $cillustrations 311 $a90-04-42916-6 320 $aIncludes bibliographical references and index. 606 $aEntomology 615 0$aEntomology. 676 $a595.703 702 $aDanilevsky$b Mikhail 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828237103321 996 $aChrysomeloidea i (vesperidae, disteniidae, cerambycidae)$94115398 997 $aUNINA