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Author: Natarajan, Arul Kumar
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 506
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Book Description
In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success.
Author: Natarajan, Arul Kumar
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 506
Get Book Here
Book Description
In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Keikhosrokiani, Pantea
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 514
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Book Description
The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers.
Author: Aouadni, Sourour
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 516
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Book Description
In an increasingly complex world, decision-makers face the challenge of optimizing multiple conflicting objectives across various scenarios. Multi-Criteria Decision-Making (MCDM) techniques have emerged as essential tools for addressing these challenges and offer methods to evaluate alternatives and minimize subjectivity. As the landscape of MCDM evolves with new approaches such as fuzzy set theory, rough set theory, and neutrosophic set theory, decision-making in situations involving varied and complex data becomes more reliable and consistent. Recent Theories and Applications for Multi-Criteria Decision-Making explores the latest trends and innovations in this field. The book includes thought-provoking input from renowned researchers who cover case studies, real-world applications, challenges, and cutting-edge methodologies. It highlights the integration of advanced technologies such as AI, big data, and IoT with MCDM, while offering practical insights into strategic decision-making in today's digital age. This volume serves as a valuable resource for scholars, practitioners, and researchers keen to improve their decision-making capacity.
Author: Bhaumik, Amiya
Publisher: IGI Global
ISBN:
Category : Science
Languages : en
Pages : 622
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Book Description
Communities around the world face an array of unprecedented challenges from climate change. From extreme weather events to biodiversity loss and resource scarcity, the impacts of climate change are far-reaching and multifaceted. Yet, amidst these challenges lies an opportunity for communities to build resilience and chart a path towards sustainable development. However, navigating this complex terrain requires actionable strategies, innovative approaches, and interdisciplinary collaboration. Community Resilience and Climate Change Challenges: Pursuit of Sustainable Development Goals (SDGs) emerges as a beacon of hope in addressing these pressing issues. By delving into the critical intersection of community resilience and the pursuit of SDGs, this book offers a comprehensive guide for empowering communities to adapt and thrive amidst climate uncertainties. Through a diverse range of practical strategies, case studies, and innovative approaches, it equips decision-makers, practitioners, and educators with the knowledge and tools needed to tackle the complex challenges of climate change and sustainable development.
Author: Kaunert, Christian
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 392
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Book Description
The destruction of millions of acres of forest land through wildfires is a global cause of concern. Artificial intelligence (AI), transformative in nature, has the potential to transcend and significantly mitigate risk factors of wildfires. AI-driven monitoring systems can detect early signs of wildfire activity, allowing for faster, more targeted responses that can minimize damage and save lives. Machine Learning and Internet of Things in Fire Ecology elucidates and explores the interface of fire ecology with AI, machine learning, and internet of things, as these technologies emerged as a pivotal domain with transformative potential. It will assist environmental-related industries in understanding the paraphernalia and dynamics of the fire ecology ecosystem. Covering topics such as AI, unmanned aerial vehicles (UAVs), and wildlife conservation, this book is an excellent resource for government officials, ecologists, academicians, policymakers, researchers, environmental specialists, industry experts, graduate and postgraduate students, and more.
Author: Natarajan, Arul Kumar
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 376
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Book Description
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.
Author: Jermsittiparsert, Kittisak
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 654
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Book Description
Amidst the complexities of modern life, the importance of human well-being in its various dimensions is a continual priority. As artificial intelligence (AI) becomes a key influence in nearly every facet of modern life, it raises essential questions about the current and future state of human health and well-being. While AI has the potential to revolutionize healthcare, enhance mental health support, and improve overall quality of life, it also presents challenges regarding privacy, ethical considerations, and the impact of automation on human relationships and mental health. Navigating these opportunities and concerns requires a balanced approach to ensure that technological advancements align with the holistic needs of individuals and communities. Physical Health, Mental Health, and Human Well-Being in the Age of AI explores the evolving landscape of health in a technology-driven world. Beyond healthcare, the book also examines the broader implications of AI on social well-being, environmental health, and the future of work and education. Through expert insights and empirical research from around the globe, this book provides invaluable knowledge for researchers and practitioners alike, and appeals to readers from a broad spectrum of disciplines.
Author: Lakshman Bulusu
Publisher: CRC Press
ISBN: 1000281930
Category : Computers
Languages : en
Pages : 241
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Book Description
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.
Author: Dimple Patil
Publisher: Deep Science Publishing
ISBN: 8198136746
Category : Computers
Languages : en
Pages : 265
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Book Description
Artificial Intelligence (AI) is evolving at an unprecedented rate, changing industries and reshaping social landscapes. However, the question still stands: how can we make sure that, even with this growth, AI stays ethical and trustworthy? In an effort to investigate this issue, the book Trustworthy Artificial Intelligence in Industry and Society provides a thorough analysis of AI's potential to promote resilience, accountability, and trust in a variety of contexts. Chapter 1 explores the essential need for transparent and interpretable AI systems, starting with the foundation of Explainable Artificial Intelligence (XAI) and laying the framework for fostering trust among users, stakeholders, and society at large. In Chapter 2, deep learning and machine learning are explored, along with their applications, methods, and implementation challenges. In Chapter 3, the book delves into the impact of artificial intelligence (AI) on Environmental, Social, and Governance (ESG) initiatives. It specifically highlights the applications of AI in the financial services and investment sectors. We look at the adoption and application of AI in the construction sector in Chapter 4, offering some insight into the drivers, patterns, and obstacles that will shape the technology's future. The use of AI to improve supply chain sustainability and revolutionize the transportation industry is covered in Chapters 5 and 6, with a focus on generative AI technologies and ethical issues. Chapter 7 explores how artificial intelligence is affecting customer relationship management, highlighting how sentiment analysis is transforming customer loyalty and experience. This book seeks to shed light on the opportunities and difficulties that artificial intelligence (AI) brings to business and society by exploring these areas.
