AI-powered business intelligence for modern organizations:
"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 main...
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| Other Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2025.
|
| Series: | Advances in business information systems and analytics (ABISA) book series.
|
| Subjects: | |
| Online Access: | DE-863 |
| Summary: | "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."-- |
| Physical Description: | 19 PDFs (376 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9798369388464 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
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| 245 | 0 | 0 | |a AI-powered business intelligence for modern organizations |c Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors. |
| 246 | 3 | |a Artificial intelligence-powered business intelligence for modern organizations | |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2025. | |
| 300 | |a 19 PDFs (376 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 490 | 1 | |a Advances in business information systems and analytics (ABISA) book series | |
| 504 | |a Includes bibliographical references and index. | ||
| 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. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 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. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 10/18/2024). | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Business intelligence. | |
| 650 | 0 | |a Business planning. | |
| 650 | 0 | |a Technological innovations |x Economic aspects. | |
| 653 | |a Artificial Intelligence (AI) | ||
| 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. | ||
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Das, Deepthi |e editor. | |
| 700 | 1 | |a Galety, Mohammad Gouse |d 1976- |e editor. | |
| 700 | 1 | |a Iwendi, Celestine |e editor. | |
| 700 | 1 | |a Natarajan, Arul Kumar |e editor. | |
| 700 | 1 | |a Shankar, Achyut |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9798369388440 |
| 830 | 0 | |a Advances in business information systems and analytics (ABISA) book series. | |
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| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-863 | ||
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| author2 | Das, Deepthi Galety, Mohammad Gouse 1976- Iwendi, Celestine Natarajan, Arul Kumar Shankar, Achyut |
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| author_facet | Das, Deepthi Galety, Mohammad Gouse 1976- Iwendi, Celestine Natarajan, Arul Kumar Shankar, Achyut |
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| collection | ZDB-98-IGB |
| contents | 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. |
| ctrlnum | (CaBNVSL)slc00006940 (OCoLC)1463451269 |
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| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00352849 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-07T12:04:13Z |
| institution | BVB |
| isbn | 9798369388464 |
| language | English |
| oclc_num | 1463451269 |
| open_access_boolean | |
| owner | DE-863 DE-BY-FWS |
| owner_facet | DE-863 DE-BY-FWS |
| physical | 19 PDFs (376 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2025 |
| publishDateSearch | 2025 |
| publishDateSort | 2025 |
| publisher | IGI Global |
| record_format | marc |
| series | Advances in business information systems and analytics (ABISA) book series. |
| series2 | Advances in business information systems and analytics (ABISA) book series |
| spelling | AI-powered business intelligence for modern organizations Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors. Artificial intelligence-powered business intelligence for modern organizations Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2025. 19 PDFs (376 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier 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. Restricted to subscribers or individual electronic text purchasers. "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."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 10/18/2024). Artificial intelligence. Business intelligence. Business planning. Technological innovations Economic aspects. Artificial Intelligence (AI) Augmented Analytics. Business Intelligence. Citizen Engagement. Consumer Vision. Customer Relationship Management (CRM) Decision-Making. E-Commerce. Financial Technologies (FinTech) Hyper-Personalization. Machine Learning (ML) Natural Language Processing (NLP) Predictive Analytics. Public Service Delivery. Sentiment Analysis. Social Media. Supply Chain Optimization. Sustainability Metrics. Volunteered Geographic Information. Electronic books. Das, Deepthi editor. Galety, Mohammad Gouse 1976- editor. Iwendi, Celestine editor. Natarajan, Arul Kumar editor. Shankar, Achyut editor. IGI Global, publisher. Print version: 9798369388440 Advances in business information systems and analytics (ABISA) book series. |
| spellingShingle | AI-powered business intelligence for modern organizations Advances in business information systems and analytics (ABISA) book series. 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. Artificial intelligence. Business intelligence. Business planning. Technological innovations Economic aspects. |
| title | AI-powered business intelligence for modern organizations |
| title_alt | Artificial intelligence-powered business intelligence for modern organizations |
| title_auth | AI-powered business intelligence for modern organizations |
| title_exact_search | AI-powered business intelligence for modern organizations |
| title_full | AI-powered business intelligence for modern organizations Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors. |
| title_fullStr | AI-powered business intelligence for modern organizations Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors. |
| title_full_unstemmed | AI-powered business intelligence for modern organizations Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors. |
| title_short | AI-powered business intelligence for modern organizations |
| title_sort | ai powered business intelligence for modern organizations |
| topic | Artificial intelligence. Business intelligence. Business planning. Technological innovations Economic aspects. |
| topic_facet | Artificial intelligence. Business intelligence. Business planning. Technological innovations Economic aspects. Electronic books. |
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