LEADER 04143nam 2200469 450 001 996547963303316 005 20230523065136.0 010 $a9783658375997$b(electronic bk.) 010 $z9783658375980 024 7 $a10.1007/978-3-658-37599-7 035 $a(MiAaPQ)EBC7206744 035 $a(Au-PeEL)EBL7206744 035 $a(CKB)26186213600041 035 $a(DE-He213)978-3-658-37599-7 035 $a(PPN)269097643 035 $a(EXLCZ)9926186213600041 100 $a20230523d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial intelligence for business analytics $ealgorithms, platforms and application scenarios /$fFelix Weber 210 1$aWiesbaden, Germany :$cSpringer,$d[2023] 210 4$dİ2023 215 $a1 online resource (146 pages) $cillustrations 311 08$aPrint version: Weber, Felix Artificial Intelligence for Business Analytics Wiesbaden : Springer Fachmedien Wiesbaden GmbH,c2023 9783658375980 320 $aIncludes bibliographical references. 327 $aBusiness Analytics -- Artificial Intelligence -- AI and BA platforms -- Technology framework and process model as reference -- Case studies on the use of AI-based business analytics. 330 $aWhile methods of artificial intelligence (AI) were until a few years ago exclusively a topic of scientific discussions, today they are increasingly finding their way into products of everyday life. At the same time, the amount of data produced and available is growing due to increasing digitization, the integration of digital measurement and control systems, and automatic exchange between devices (Internet of Things). In the future, the use of business intelligence (BI) and a look into the past will no longer be sufficient for most companies. Instead, business analytics, i.e., predictive and predictive analyses and automated decisions, will be needed to stay competitive in the future. The use of growing amounts of data is a significant challenge and one of the most important areas of data analysis is represented by artificial intelligence methods. This book provides a concise introduction to the essential aspects of using artificial intelligence methods for business analytics, presents machine learning and the most important algorithms in a comprehensible form based on the business analytics technology framework, and shows application scenarios from various industries. In addition, it provides the Business Analytics Model for Artificial Intelligence, a reference procedure model for structuring BA and AI projects in the company. The Content Business Analytics Artificial Intelligence AI and BA platforms Technology framework and procedure model as reference Case studies on the use of AI-based business analytics The Author Felix Weber is a researcher at the University of Duisburg-Essen with a focus on digitalization, artificial intelligence, price, promotion, assortment management, and transformation management. At the Chair of Business Informatics and Integrated Information Systems, he founded the Retail Artificial Intelligence Lab (retAIL). At the same time, he also worked on various jobs as a consultant for SAP systems in retail, Head of Data Science and as Head of ERP. He thus combines current practice with scientific research in this subfield. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. 606 $aArtificial intelligence 606 $aBusiness$xData processing 615 0$aArtificial intelligence. 615 0$aBusiness$xData processing. 676 $a006.3 700 $aWeber$b Felix$01311654 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a996547963303316 996 $aArtificial Intelligence for Business Analytics$93061012 997 $aUNISA