LEADER 03818oam 2200493I 450 001 9910860853103321 005 20240513124032.0 010 $a1-00-312208-6 010 $a1-000-28195-7 010 $a1-003-12208-6 010 $a1-000-28193-0 024 7 $a10.1201/9781003122081. 035 $a(CKB)4100000011393661 035 $a(MiAaPQ)EBC6313515 035 $a(OCoLC)1203551178 035 $a(OCoLC-P)1203551178 035 $a(FlBoTFG)9781003122081 035 $a(EXLCZ)994100000011393661 100 $a20200830d2020 my 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAI Meets BI $eArtificial Intelligence and Business Intelligence /$fLakshman Bulusu, Rosendo Abellera 205 $a1st ed. 210 1$aBoca Raton :$cAuerbach Publications,$d2020. 215 $a1 online resource (241 pages) 300 $aIncludes index. 311 $a0-367-64381-2 311 $a0-367-33260-4 327 $aChapter 1 Introduction; Chapter 2 AI and AI-Powered Analytics; Chapter 3 Industry Uses Cases of Enterprise BI--A Business Perspective; Chapter 4 Industry Use Cases of Enterprise BI--The AI-Way of Implementation; Chapter 5 What's Next in AI Meets BI? 330 $aWith the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI. 606 $aBusiness intelligence$xData processing 615 0$aBusiness intelligence$xData processing. 676 $a658.472 700 $aLakshman$b Bulusu$01629307 702 $aAbellera$b Rosendo 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9910860853103321 996 $aAI Meets BI$94167687 997 $aUNINA