000 04388cam a2200529Ii 4500
001 9781003122081
003 FlBoTFG
005 20220509193136.0
006 m d
007 cr |||||||||||
008 200830s2020 flu go 000 0 eng d
040 _aOCoLC-P
_beng
_cOCoLC-P
020 _a1000281957
_q(EPUB)
020 _a9781003122081
_q(electronic bk.)
020 _a1003122086
_q(electronic bk.)
020 _a9781000281941
_q(electronic bk. : Mobipocket)
020 _a1000281949
_q(electronic bk. : Mobipocket)
020 _a9781000281934
_q(electronic bk. : PDF)
020 _a1000281930
_q(electronic bk. : PDF)
020 _a9781000281958
_q(electronic bk.)
024 7 _a10.1201/9781003122081.
_2doi
035 _a(OCoLC)1203551178
035 _a(OCoLC-P)1203551178
050 4 _aHD38.7
072 7 _aCOM
_x004000
_2bisacsh
072 7 _aCOM
_x021030
_2bisacsh
072 7 _aBUS
_x083000
_2bisacsh
072 7 _aUYQ
_2bicssc
082 0 4 _a658.472028563
_223
100 1 _aLakshman, Bulusu,
_eauthor.
245 1 0 _aAI Meets BI :
_bArtificial Intelligence and Business Intelligence /
_cLakshman Bulusu, Rosendo Abellera.
264 1 _aBoca Raton :
_bAuerbach Publications,
_c2020.
300 _a1 online resource (220 pages)
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
505 0 _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?
520 _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.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aBusiness intelligence
_xData processing.
650 0 _aArtificial intelligence.
650 7 _aCOMPUTERS / Artificial Intelligence
_2bisacsh
650 7 _aCOMPUTERS / Database Management / Data Mining
_2bisacsh
650 7 _aBUSINESS & ECONOMICS / Information Management
_2bisacsh
700 1 _aAbellera, Rosendo,
_eauthor.
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003122081
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c130771
_d130771