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AI meets BIartificial intelligence and business intelligence /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	AI meets BILakshman Bulusu, Rosendo Abellera.
其他題名:	artificial intelligence and business intelligence /
作者:	Lakshman, Bulusu.
其他作者:	Abellera, Rosendo.
出版者:	Boca Raton, FL :CRC Press,c2021.
面頁冊數:	1 online resource (220 p.) :ill.
附註:	"An Auerbach book."
標題:	Business intelligenceData processing.
電子資源:	https://www.taylorfrancis.com/books/9781003122081
ISBN:	9781003122081$q(electronic bk.)

AI meets BIartificial intelligence and business intelligence /
Lakshman, Bulusu.

AI meets BIartificial intelligence and business intelligence /[electronic resource] :Lakshman Bulusu, Rosendo Abellera. - Boca Raton, FL :CRC Press,c2021. - 1 online resource (220 p.) :ill.

"An Auerbach book."

Includes bibliographical references and index.

With 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.

ISBN: 9781003122081$q(electronic bk.)Subjects--Topical Terms:

283177
Business intelligence
--Data processing.

LC Class. No.: HD38.7

Dewey Class. No.: 658.472028563

AI meets BIartificial intelligence and business intelligence /
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300 $a 1 online resource (220 p.) : $b ill.
500 $a "An Auerbach book."
504 $a Includes bibliographical references and index.
520 $a With 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 $a Description based on print version record.
650 0 $a Business intelligence $x Data processing. $3 283177
650 0 $a Artificial intelligence. $3 194058
700 1 $a Abellera, Rosendo. $3 803942
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