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Author: Thorsten Heilig
Publisher: John Wiley & Sons
ISBN: 1394185065
Category : Business & Economics
Languages : en
Pages : 247
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Book Description
Dramatically improve your decisions with data and AI In Decision Intelligence: How to Transform Your Team and Organization with AI-Driven Decision-Making, a team of pioneering decision and AI strategists delivers a digestible and hands-on resource for professionals at every part of the decision-making journey. The book discusses the latest technology and approaches that bridge the gap between behavioral science, data science, and technological innovation. Discover how leaders from various industries and environments are using data and AI to make better future decisions, taking both human as well as business factors into account. This book covers: A demystifying behind-the-scenes peek inside how AI models, forecasts, and optimization for business challenges really work, and why they open up entirely new possibilities. A business-ready introduction to decision intelligence, exploring why traditional decision-making strategies are outdated and how to transition to decision-intelligence. The evolution of Decision Intelligence, coming from analytics and modern techniques like process mining and robotic process automation An examination of decision intelligence at the organizational level, including discussions of agile transformation, transparent organizational culture, and why psychological safety is a crucial enabler for new ways of decision-making in modern companies An overview of why (and where exactly) AI still needs human expertise and how to incorporate this topic in daily planning and decision making Decision Intelligence is essential reading for managers, executives, board members, other business leaders and soon-to-be leaders looking to improve the quality, adaptability, and speed of their decision-making.
Author: Thorsten Heilig
Publisher: John Wiley & Sons
ISBN: 1394185065
Category : Business & Economics
Languages : en
Pages : 247
Get Book Here
Book Description
Dramatically improve your decisions with data and AI In Decision Intelligence: How to Transform Your Team and Organization with AI-Driven Decision-Making, a team of pioneering decision and AI strategists delivers a digestible and hands-on resource for professionals at every part of the decision-making journey. The book discusses the latest technology and approaches that bridge the gap between behavioral science, data science, and technological innovation. Discover how leaders from various industries and environments are using data and AI to make better future decisions, taking both human as well as business factors into account. This book covers: A demystifying behind-the-scenes peek inside how AI models, forecasts, and optimization for business challenges really work, and why they open up entirely new possibilities. A business-ready introduction to decision intelligence, exploring why traditional decision-making strategies are outdated and how to transition to decision-intelligence. The evolution of Decision Intelligence, coming from analytics and modern techniques like process mining and robotic process automation An examination of decision intelligence at the organizational level, including discussions of agile transformation, transparent organizational culture, and why psychological safety is a crucial enabler for new ways of decision-making in modern companies An overview of why (and where exactly) AI still needs human expertise and how to incorporate this topic in daily planning and decision making Decision Intelligence is essential reading for managers, executives, board members, other business leaders and soon-to-be leaders looking to improve the quality, adaptability, and speed of their decision-making.
Author: Pamela Baker
Publisher: John Wiley & Sons
ISBN: 1119824842
Category : Computers
Languages : en
Pages : 323
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Book Description
Learn to use, and not be used by, data to make more insightful decisions The availability of data and various forms of AI unlock countless possibilities for business decision makers. But what do you do when you feel pressured to cede your position in the decision-making process altogether? Decision Intelligence For Dummies pumps the brakes on the growing trend to take human beings out of the decision loop and walks you through the best way to make data-informed but human-driven decisions. The book shows you how to achieve maximum flexibility by using every available resource, and not just raw data, to make the most insightful decisions possible. In this timely book, you’ll learn to: Make data a means to an end, rather than an end in itself, by expanding your decision-making inquiries Find a new path to solid decisions that includes, but isn’t dominated, by quantitative data Measure the results of your new framework to prove its effectiveness and efficiency and expand it to a whole team or company Perfect for business leaders in technology and finance, Decision Intelligence For Dummies is ideal for anyone who recognizes that data is not the only powerful tool in your decision-making toolbox. This book shows you how to be guided, and not ruled, by the data.
Author: Gloria Phillips-Wren
Publisher: Springer
ISBN: 3540768297
Category : Technology & Engineering
Languages : en
Pages : 414
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Book Description
Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.
Author: Miriam O'Callaghan
Publisher: CRC Press
ISBN: 1000880001
Category : Business & Economics
Languages : en
Pages : 280
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Book Description
1. Provides a multidisciplinary approach of building knowledge on DI; 2. Discusses the limits of the human brain and why computer models are better at making decisions; 3. Covers agent programs for AI-powered decision-making agents; 4. Presents a DI framework - flowchart and figures; 5. Includes detailed and comprehensive information on DI tools and technologies; 6. Gives an ethics-focused approach to building DI systems for the protection of human rights and wellbeing.
Author: Carlo Vercellis
Publisher: John Wiley & Sons
ISBN: 1119965470
Category : Mathematics
Languages : en
Pages : 314
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Book Description
Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.
Author: B. K. Murthy
Publisher: Springer Nature
ISBN: 9819959977
Category : Technology & Engineering
Languages : en
Pages : 416
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Book Description
This book comprises the select peer-reviewed proceedings of the 3rd International Conference on Information Technology (InCITe-2023). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in decision intelligence, deep learning, machine learning, artificial intelligence, data science, and enabling technologies for IoT, blockchain, and other futuristic computational technologies. It covers various topics that span cutting-edge, collaborative technologies and areas of computation. The content would serve as a rich knowledge repository on information & communication technologies, neural networks, fuzzy systems, natural language processing, data mining & warehousing, big data analytics, cloud computing, security, social networks, and intelligence, decision-making, and modeling, information systems, and IT architectures. This book provides a valuable resource for those in academia and industry.
Author: P. Mary Jeyanthi
Publisher: Springer Nature
ISBN: 3030827631
Category : Technology & Engineering
Languages : en
Pages : 236
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Book Description
This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context.
Author: L. Y. Pratt
Publisher: "O'Reilly Media, Inc."
ISBN: 1098139623
Category :
Languages : en
Pages : 270
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Book Description
Decision intelligence (DI) has been widely named as a top technology trend for several years, and Gartner reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies. But until now, there has been little practical guidance for organizations to formalize decision making and integrate their decisions with data. With this book, authors L. Y. Pratt and N. E. Malcolm fill this gap. They present a step-by-step method for integrating technology into decisions that bridge from actions to desired outcomes, with a focus on systems that act in an advisory, human-in-the-loop capacity to decision makers. This handbook addresses three widespread data-driven decision-making problems: How can decision makers use data and technology to ensure desired outcomes? How can technology teams communicate effectively with decision makers to maximize the return on their data and technology investments? How can organizational decision makers assess and improve their decisions over time?
Author: Daniel Brown
Publisher: Elsevier
ISBN: 1780630670
Category : Business & Economics
Languages : en
Pages : 167
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Book Description
Aimed at information managers in organisations including local/state government, libraries and financial services. Mastering Information Retrieval and Probabilistic Decision Intelligence Technology reviews the management of information and its focus to people empowered to make decisions. It provides managers and students of information with the resources to understand and start to deploy information retrieval systems throughout their organisation and the tools to respond effectively to the enormous developments in new technologies. - Written by an expert practitioner in the field - Helps to summarise and explain the basic issues - Covers both benefits and challenges likely to be encountered in implementing an Information Retrieval system
Author: Olivier Sigaud
Publisher: John Wiley & Sons
ISBN: 1118620100
Category : Technology & Engineering
Languages : en
Pages : 367
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Book Description
Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as reinforcement learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in artificial intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, reinforcement learning, partially observable MDPs, Markov games and the use of non-classical criteria). It then presents more advanced research trends in the field and gives some concrete examples using illustrative real life applications.
