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AI-powered business intelligence for modern organizations

Record Type:	Electronic resources : Monograph/item
Title/Author:	AI-powered business intelligence for modern organizations/ Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors.
remainder title:	Artificial intelligence-powered business intelligence for modern organizations
other author:	Das, Deepthi.
Published:	Hershey, Pennsylvania :IGI Global, : 2025.,
Description:	1 online resource (376 p.)
[NT 15003449]:	Foreword -- Preface -- Chapter 1. Integrating Sustainability Metrics Into Business Intelligence: Environmental, Social, and Governance (ESG) Factors -- Chapter 2. Leveraging AI and Machine Learning for Predictive Analytics in Business Intelligence -- Chapter 3. The Role of AI and ML in Shaping Predictive Analytics for Modern Business Intelligence: Techniques, Challenges, and Applications for Data-Driven Decision-Making -- Chapter 4. DDM: Data-Driven Marketing Using AI, ML, and Big Data -- Chapter 5. Enabling Hyper-Personalization in AI-Powered BI Systems: Augmented Analytics -- Chapter 6. Personalization and Customer Relationship Management (CRM) in AI-Powered Business Intelligence -- Chapter 7. Optimizing Supply Chain With AI-Powered BI Systems -- Chapter 8. Security, Transparency, and Traceability: Role of Blockchain in AI-Powered Supply Chain -- Chapter 9. Utilizing Business Intelligence and Machine Learning in CRM Data to Reduce Customer Churn in E-commerce Platforms -- Chapter 10. Illuminating the Convergence of Artificial Intelligence (AI) and Business Intelligence (BI) in E-Commerce and Fin-Tech in India -- Chapter 11. Impact of Artificial Intelligence on Organizational Performance of Agritech Firm -- Chapter 12. Future Directions and Trends in AI-Powered Business Intelligence -- Compilation of References -- About the Contributors -- Index.
Subject:	Business intelligence. -
Online resource:	https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8844-0
ISBN:	9798369388464

AI-powered business intelligence for modern organizations
AI-powered business intelligence for modern organizations[electronic resource] /Artificial intelligence-powered business intelligence for modern organizationsArul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (376 p.) - Advances in business information systems and analytics (ABISA) book series. - Advances in business information systems and analytics (ABISA) book series..

Includes bibliographical references and index.

Foreword -- Preface -- Chapter 1. Integrating Sustainability Metrics Into Business Intelligence: Environmental, Social, and Governance (ESG) Factors -- Chapter 2. Leveraging AI and Machine Learning for Predictive Analytics in Business Intelligence -- Chapter 3. The Role of AI and ML in Shaping Predictive Analytics for Modern Business Intelligence: Techniques, Challenges, and Applications for Data-Driven Decision-Making -- Chapter 4. DDM: Data-Driven Marketing Using AI, ML, and Big Data -- Chapter 5. Enabling Hyper-Personalization in AI-Powered BI Systems: Augmented Analytics -- Chapter 6. Personalization and Customer Relationship Management (CRM) in AI-Powered Business Intelligence -- Chapter 7. Optimizing Supply Chain With AI-Powered BI Systems -- Chapter 8. Security, Transparency, and Traceability: Role of Blockchain in AI-Powered Supply Chain -- Chapter 9. Utilizing Business Intelligence and Machine Learning in CRM Data to Reduce Customer Churn in E-commerce Platforms -- Chapter 10. Illuminating the Convergence of Artificial Intelligence (AI) and Business Intelligence (BI) in E-Commerce and Fin-Tech in India -- Chapter 11. Impact of Artificial Intelligence on Organizational Performance of Agritech Firm -- Chapter 12. Future Directions and Trends in AI-Powered Business Intelligence -- Compilation of References -- About the Contributors -- Index.

"Technology's rapid advancement has revolutionized how organizations gather, analyze, and utilize data. In this dynamic landscape, integrating artificial intelligence (AI) into business intelligence (BI) systems has emerged as a critical factor for driving informed decision-making and maintaining competitive advantage. This integration allows business to respond quickly to market changes, personalize customer experiences, and optimize operations with greater precision. As AI-driven BI tools continue to evolve, they empower organizations to harness vast amounts of data more effectively, making strategic decisions that are both timely and data-driven, thereby securing their position in an increasingly competitive marketplace. AI-Powered Business Intelligence for Modern Organizations provides a comprehensive overview of this transformative intersection, addressing the diverse challenges, opportunities, and future trends in this field. By exploring the integration of AI into BI systems, the text delves into how advanced analytics, machine learning, and automation are reshaping the way businesses operate. Covering topics such as augmented analytics, decision-making, and sustainability metrics, this book is an excellent resource for business leaders and executives, data scientists and analysts, IT and technology managers, academicians, researchers, graduate and postgraduate students, consultants, industry experts, and more."--

Mode of access: World Wide Web.

ISBN: 9798369388464Subjects--Topical Terms:

669648
Business intelligence.
Subjects--Index Terms:

Artificial Intelligence (AI)Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HD38.7 / .A37 2025eb

Dewey Class. No.: 658.472

AI-powered business intelligence for modern organizations
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505 0 $a Foreword -- Preface -- Chapter 1. Integrating Sustainability Metrics Into Business Intelligence: Environmental, Social, and Governance (ESG) Factors -- Chapter 2. Leveraging AI and Machine Learning for Predictive Analytics in Business Intelligence -- Chapter 3. The Role of AI and ML in Shaping Predictive Analytics for Modern Business Intelligence: Techniques, Challenges, and Applications for Data-Driven Decision-Making -- Chapter 4. DDM: Data-Driven Marketing Using AI, ML, and Big Data -- Chapter 5. Enabling Hyper-Personalization in AI-Powered BI Systems: Augmented Analytics -- Chapter 6. Personalization and Customer Relationship Management (CRM) in AI-Powered Business Intelligence -- Chapter 7. Optimizing Supply Chain With AI-Powered BI Systems -- Chapter 8. Security, Transparency, and Traceability: Role of Blockchain in AI-Powered Supply Chain -- Chapter 9. Utilizing Business Intelligence and Machine Learning in CRM Data to Reduce Customer Churn in E-commerce Platforms -- Chapter 10. Illuminating the Convergence of Artificial Intelligence (AI) and Business Intelligence (BI) in E-Commerce and Fin-Tech in India -- Chapter 11. Impact of Artificial Intelligence on Organizational Performance of Agritech Firm -- Chapter 12. Future Directions and Trends in AI-Powered Business Intelligence -- Compilation of References -- About the Contributors -- Index.
520 3 $a "Technology's rapid advancement has revolutionized how organizations gather, analyze, and utilize data. In this dynamic landscape, integrating artificial intelligence (AI) into business intelligence (BI) systems has emerged as a critical factor for driving informed decision-making and maintaining competitive advantage. This integration allows business to respond quickly to market changes, personalize customer experiences, and optimize operations with greater precision. As AI-driven BI tools continue to evolve, they empower organizations to harness vast amounts of data more effectively, making strategic decisions that are both timely and data-driven, thereby securing their position in an increasingly competitive marketplace. AI-Powered Business Intelligence for Modern Organizations provides a comprehensive overview of this transformative intersection, addressing the diverse challenges, opportunities, and future trends in this field. By exploring the integration of AI into BI systems, the text delves into how advanced analytics, machine learning, and automation are reshaping the way businesses operate. Covering topics such as augmented analytics, decision-making, and sustainability metrics, this book is an excellent resource for business leaders and executives, data scientists and analysts, IT and technology managers, academicians, researchers, graduate and postgraduate students, consultants, industry experts, and more."-- $c Provided by publisher.
538 $a Mode of access: World Wide Web.
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650 0 $a Artificial intelligence. $3 516317
650 0 $a Business planning. $3 602297
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653 $a Augmented Analytics.
653 $a Business Intelligence.
653 $a Citizen Engagement.
653 $a Consumer Vision.
653 $a Customer Relationship Management (CRM)
653 $a Decision-Making.
653 $a E-Commerce.
653 $a Financial Technologies (FinTech)
653 $a Hyper-Personalization.
653 $a Machine Learning (ML)
653 $a Natural Language Processing (NLP)
653 $a Predictive Analytics.
653 $a Public Service Delivery.
653 $a Sentiment Analysis.
653 $a Social Media.
653 $a Supply Chain Optimization.
653 $a Sustainability Metrics.
653 $a Volunteered Geographic Information.
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700 1 $a Das, Deepthi. $3 3793213
700 1 $a Iwendi, Celestine. $3 3666605
700 1 $a Galety, Mohammad Gouse, $d 1976- $3 3793230
700 1 $a Natarajan, Arul Kumar. $3 3793215
700 1 $a Shankar, Achyut. $3 3793212
710 2 $a IGI Global. $3 1361470
776 0 8 $i Print version: $z 9798369388440
830 0 $a Advances in business information systems and analytics (ABISA) book series. $3 3310827
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