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Deciphering Data Architectures
by James SerraData fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each. James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You'll learn what data lakehouses can help you achieve, as well as how to distinguish data mesh hype from reality. Best of all, you'll be able to determine the most appropriate data architecture for your needs. With this book, you'll:Gain a working understanding of several data architecturesLearn the strengths and weaknesses of each approachDistinguish data architecture theory from realityPick the best architecture for your use caseUnderstand the differences between data warehouses and data lakesLearn common data architecture concepts to help you build better solutionsExplore the historical evolution and characteristics of data architecturesLearn essentials of running an architecture design session, team organization, and project success factorsFree from product discussions, this book will serve as a timeless resource for years to come.
Deciphering Object-Oriented Programming with C++: A practical, in-depth guide to implementing object-oriented design principles to create robust code
by Dorothy R. KirkEmbrace object-oriented programming and explore language complexities, design patterns, and smart programming techniques using this hands-on guide with C++ 20 compliant examplesKey FeaturesApply object-oriented design concepts in C++ using direct language features and refined programming techniquesDiscover sophisticated programming solutions with nuances to become an efficient programmerExplore design patterns as proven solutions for writing scalable and maintainable C++ softwareBook DescriptionEven though object-oriented software design enables more easily maintainable code, companies choose C++ as an OO language for its speed. Object-oriented programming in C++ is not automatic – it is crucial to understand OO concepts and how they map to both C++ language features and OOP techniques. Distinguishing your code by utilizing well-tested, creative solutions, which can be found in popular design patterns, is crucial in today's marketplace. This book will help you to harness OOP in C++ to write better code.Starting with the essential C++ features, which serve as building blocks for the key chapters, this book focuses on explaining fundamental object-oriented concepts and shows you how to implement them in C++. With the help of practical code examples and diagrams, you'll learn how and why things work. The book's coverage furthers your C++ repertoire by including templates, exceptions, operator overloading, STL, and OO component testing. You'll discover popular design patterns with in-depth examples and understand how to use them as effective programming solutions to solve recurring OOP problems.By the end of this book, you'll be able to employ essential and advanced OOP concepts to create enduring and robust software.What you will learnQuickly learn core C++ programming skills to develop a base for essential OOP features in C++Implement OO designs using C++ language features and proven programming techniquesUnderstand how well-designed, encapsulated code helps make more easily maintainable softwareWrite robust C++ code that can handle programming exceptionsDesign extensible and generic code using templatesApply operator overloading, utilize STL, and perform OO component testingExamine popular design patterns to provide creative solutions for typical OO problemsWho this book is forProgrammers wanting to utilize C++ for OOP will find this book essential to understand how to implement OO designs in C++ through both language features and refined programming techniques while creating robust and easily maintainable code. This OOP book assumes prior programming experience; however, if you have limited or no prior C++ experience, the early chapters will help you learn essential C++ skills to serve as the basis for the many OOP sections, advanced features, and design patterns.
Decision Analytics Applications in Industry (Asset Analytics)
by Uday Kumar P. K. Kapur Gurinder Singh Yury S. KlochkovThis book presents a range of qualitative and quantitative analyses in areas such as cybersecurity, sustainability, multivariate analysis, customer satisfaction, parametric programming, software reliability growth modeling, and blockchain technology, to name but a few. It also highlights integrated methods and practices in the areas of machine learning and genetic algorithms. After discussing applications in supply chains and logistics, cloud computing, six sigma, production management, big data analysis, satellite imaging, game theory, biometric systems, quality, and system performance, the book examines the latest developments and breakthroughs in the field of science and technology, and provides novel problem-solving methods. The themes discussed in the book link contributions by researchers and practitioners from different branches of engineering and management, and hailing from around the globe. These contributions provide scholars with a platform to derive maximum utility in the area of analytics by subscribing to the idea of managing business through system sciences, operations, and management. Managers and decision-makers can learn a great deal from the respective chapters, which will help them devise their own business strategies and find real-world solutions to complex industrial problems.
Decision Analytics for Sustainable Development in Smart Society 5.0: Issues, Challenges and Opportunities (Asset Analytics)
by Vikram Bali Vishal Bhatnagar Joan Lu Kakoli BanerjeeThis book covers sustainable development in smart society’s 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.
Decision and Control in Hybrid Wind Farms (Studies in Systems, Decision and Control #253)
by Harsh S. Dhiman Dipankar DebThis book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecasting can be compensated for by pumping power from a reserve capacity to the grid using a battery energy storage system (BESS). Alternatives based on penalty cost are assessed using certain criteria, and MCDM methods are used to evaluate the best choice. Further, considering the randomness in the dynamic phenomenon in wind farms, a fuzzy MCDM approach is applied during the decision-making process to evaluate the best alternative for hybrid wind farm operation. Case studies from wind farms in the USA are presented, together with numerical solutions to the problem. In turn, the second part deals with the control aspect, and especially with yaw angle control, which facilitates power maximization at wind farms. A novel transfer function-based methodology is presented that controls the wake center of the upstream turbine(s); lidar-based numerical simulation is carried out for wind farm layouts; and an adaptive control strategy is implemented to achieve the desired yaw angle for upstream turbines. The proposed methodology is tested for two wind farm layouts. Wake management is also implemented for hybrid wind farms where BESS life enhancement is studied. The effect of yaw angle on the operational cost of BESS is assessed, and case studies for wind farm datasets from the USA and Denmark are discussed. Overall, the book provides a comprehensive guide to decision and control aspects for hybrid wind farms, which are particularly important from an industrial standpoint.
Decision and Game Theory for Security: 10th International Conference, GameSec 2019, Stockholm, Sweden, October 30 – November 1, 2019, Proceedings (Lecture Notes in Computer Science #11836)
by Tansu Alpcan Yevgeniy Vorobeychik John S. Baras György DánThis book constitutes the refereed proceedings of the 10th International Conference on Decision and Game Theory for Security, GameSec 2019,held in Stockholm, Sweden, in October 2019.The 21 full papers presented together with 11 short papers were carefully reviewed and selected from 47 submissions.The papers focus on protection of heterogeneous, large-scale and dynamic cyber-physical systems as well as managing security risks faced by critical infrastructures through rigorous and practically-relevant analytical methods.
Decision and Game Theory for Security: 12th International Conference, GameSec 2021, Virtual Event, October 25–27, 2021, Proceedings (Lecture Notes in Computer Science #13061)
by Branislav Bošanský Cleotilde Gonzalez Stefan Rass Arunesh SinhaThis book constitutes the refereed proceedings of the 12th International Conference on Decision and Game Theory for Security, GameSec 2021,held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 20 full papers presented were carefully reviewed and selected from 37 submissions. The papers focus on Theoretical Foundations in Equilibrium Computation; Machine Learning and Game Theory; Ransomware; Cyber-Physical Systems Security; Innovations in Attacks and Defenses.
Decision and Game Theory for Security: 9th International Conference, GameSec 2018, Seattle, WA, USA, October 29–31, 2018, Proceedings (Lecture Notes in Computer Science #11199)
by Linda Bushnell Radha Poovendran Tamer BaşarThe 28 revised full papers presented together with 8 short papers were carefully reviewed and selected from 44 submissions.Among the topical areas covered were: use of game theory; control theory; and mechanism design for security and privacy; decision making for cybersecurity and security requirements engineering; security and privacy for the Internet-of-Things; cyber-physical systems; cloud computing; resilient control systems, and critical infrastructure; pricing; economic incentives; security investments, and cyber insurance for dependable and secure systems; risk assessment and security risk management; security and privacy of wireless and mobile communications, including user location privacy; sociotechnological and behavioral approaches to security; deceptive technologies in cybersecurity and privacy; empirical and experimental studies with game, control, or optimization theory-based analysis for security and privacy; and adversarial machine learning and crowdsourcing, and the role of artificial intelligence in system security.
Decision and Game Theory for Security: 13th International Conference, GameSec 2022, Pittsburgh, PA, USA, October 26–28, 2022, Proceedings (Lecture Notes in Computer Science #13727)
by Fei Fang Haifeng Xu Yezekael HayelThis book constitutes the refereed proceedings of the 13th International Conference on Decision and Game Theory for Security, GameSec 2022, held in October 2022 in Pittsburgh, PA, USA. The 15 full papers presented were carefully reviewed and selected from 39 submissions. The papers are grouped thematically on: deception in security; planning and learning in dynamic environments; security games; adversarial learning and optimization; novel applications and new game models.
Decision and Game Theory for Security: 14th International Conference, GameSec 2023, Avignon, France, October 18–20, 2023, Proceedings (Lecture Notes in Computer Science #14167)
by Jie Fu Tomas Kroupa Yezekael HayelThis book constitutes the refereed proceedings of the 14th International Conference on Decision and Game Theory for Security, GameSec 2023, held in Avignon, France, during October 18–20, 2023.The 19 full papers and 4 short papers included in this book were carefully reviewed and selected from 33 submissions. They were organized in topical sections as follows: Mechanism design and imperfect information, Security Games, Learning in security games, Cyber deception, Economics of security, Information and privacy and Short articles.
Decision and Game Theory for Security
by Mhr Khouzani Emmanouil Panaousis George TheodorakopoulosThis book constitutes the refereed proceedings of the 6th International Conference on Decision and Game Theory for Security, GameSec 2015, held in London, UK, in November 2015. The 16 revised full papers presented together with 5 short papers were carefully reviewed and selected from 37 submissions. Game and decision theory has emerged as a valuable systematic framework with powerful analytical tools in dealing with the intricacies involved in making sound and sensible security decisions. For instance, game theory provides methodical approaches to account for interdependencies of security decisions, the role of hidden and asymmetric information, the perception of risks and costs in human behaviour, the incentives/limitations of the attackers, and much more. Combined with our classical approach to computer and network security, and drawing from various fields such as economic, social and behavioural sciences, game and decision theory is playing a fundamental role in the development of the pillars of the "science of security".
Decision and Game Theory for Security: 15th International Conference, GameSec 2024, New York City, NY, USA, October 16–18, 2024, Proceedings (Lecture Notes in Computer Science #14908)
by Arunesh Sinha Jie Fu Quanyan Zhu Tao ZhangThis book constitutes the refereed proceedings of the 15th International Conference on Decision and Game Theory for Security, GameSec 2024, which took place in New York City, USA, in October 2024. The 15 full papers included in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections as follows: systems security; economics; equilibrium and control; cyber deception; network and privacy; adversarial machine learning; and cyber-physical systems.
Decision and Game Theory for Security
by Quanyan Zhu Tansu Alpcan Emmanouil Panaousis Milind Tambe William CaseyThis book constitutes the refereed proceedings of the 6th International Conference on Decision and Game Theory for Security, GameSec 2015, held in London, UK, in November 2015. The 16 revised full papers presented together with 5 short papers were carefully reviewed and selected from 37 submissions. Game and decision theory has emerged as a valuable systematic framework with powerful analytical tools in dealing with the intricacies involved in making sound and sensible security decisions. For instance, game theory provides methodical approaches to account for interdependencies of security decisions, the role of hidden and asymmetric information, the perception of risks and costs in human behaviour, the incentives/limitations of the attackers, and much more. Combined with our classical approach to computer and network security, and drawing from various fields such as economic, social and behavioural sciences, game and decision theory is playing a fundamental role in the development of the pillars of the "science of security".
Decision and Game Theory for Security: 11th International Conference, GameSec 2020, College Park, MD, USA, October 28–30, 2020, Proceedings (Lecture Notes in Computer Science #12513)
by Quanyan Zhu John S. Baras Radha Poovendran Juntao ChenThis book constitutes the refereed proceedings of the 11th International Conference on Decision and Game Theory for Security, GameSec 2020,held in College Park, MD, USA, in October 2020. Due to COVID-19 pandemic the conference was held virtually The 21 full papers presented together with 2 short papers were carefully reviewed and selected from 29 submissions. The papers focus on machine learning and security; cyber deception; cyber-physical systems security; security of network systems; theoretic foundations of security games; emerging topics.
Decision and Game Theory in Management With Intuitionistic Fuzzy Sets
by Deng-Feng LiThe focus of this book is on establishing theories and methods of both decision and game analysis in management using intuitionistic fuzzy sets. It proposes a series of innovative theories, models and methods such as the representation theorem and extension principle of intuitionistic fuzzy sets, ranking methods of intuitionistic fuzzy numbers, non-linear and linear programming methods for intuitionistic fuzzy multi-attribute decision making and (interval-valued) intuitionistic fuzzy matrix games. These theories and methods form the theory system of intuitionistic fuzzy decision making and games, which is not only remarkably different from those of the traditional, Bayes and/or fuzzy decision theory but can also provide an effective and efficient tool for solving complex management problems. Since there is a certain degree of inherent hesitancy in real-life management, which cannot always be described by the traditional mathematical methods and/or fuzzy set theory, this book offers an effective approach to using the intuitionistic fuzzy set expressed with membership and non-membership functions. This book is addressed to all those involved in theoretical research and practical applications from a variety of fields/disciplines: decision science, game theory, management science, fuzzy sets, operational research, applied mathematics, systems engineering, industrial engineering, economics, etc.
Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions (Intelligent Systems Reference Library #156)
by Igor Chikalov Mikhail Moshkov Fawaz Alsolami Mohammad AzadThe results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The authors consider various examples of problems and corresponding decision tables with many-valued decisions, discuss the difference between decision and inhibitory trees and rules, and develop tools for their analysis and design. Applications include the study of totally optimal (optimal in relation to a number of criteria simultaneously) decision and inhibitory trees and rules; the comparison of greedy heuristics for tree and rule construction as single-criterion and bi-criteria optimization algorithms; and the development of a restricted multi-pruning approach used in classification and knowledge representation.
Decision-Based Design
by Christopher Hoyle Henk Jan Wassenaar Wei ChenBuilding upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design. Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, and the design case studies for integrating consumer preference modeling into the enterprise-driven DBD framework. Methods for identifying key attributes, optimal design of human appraisal experiments, data collection, data analysis, and demand model estimation are presented and illustrated using engineering design case studies. The scope of the chapters also provides: A rigorous framework of integrating the interests from both producer and consumers in engineering design, Analytical techniques of consumer choice modelling to forecast the impact of engineering decisions, Methods for synthesizing business and engineering models in multidisciplinary design environments, and Examples of effective application of Decision-Based Design supported by case studies. No matter whether you are an engineer facing decisions in consumer related product design, an instructor or student of engineering design, or a researcher exploring the role of decision making and consumer choice modelling in design, Decision-Based Design: Integrating Consumer Preferences into Engineering Design provides a reliable reference over a range of key topics.
Decision Economics: Complexity of Decisions and Decisions for Complexity (Advances in Intelligent Systems and Computing #1009)
by Shu-Heng Chen Juan Manuel Corchado Edgardo BucciarelliThis book is based on the International Conference on Decision Economics (DECON 2019). Highlighting the fact that important decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, psychology, small and international business, management, operations, and production, the book focuses on analytics as an emerging synthesis of sophisticated methodology and large data systems used to guide economic decision-making in an increasingly complex business environment.DECON 2019 was organised by the University of Chieti-Pescara (Italy), the National Chengchi University of Taipei (Taiwan), and the University of Salamanca (Spain), and was held at the Escuela politécnica Superior de Ávila, Spain, from 26th to 28th June, 2019. Sponsored by IEEE Systems Man and Cybernetics Society, Spain Section Chapter, and IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA-and-APPIA, with the funding supporting of the Junta de Castilla y León, Spain (ID: SA267P18-Project co-financed with FEDER funds)
Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions (Advances in Intelligent Systems and Computing #805)
by Edgardo Bucciarelli Shu-Heng Chen Juan Manuel CorchadoThe special session on Decision Economics (DECON) is a scientific forum held annually, which is focused on sharing ideas, projects, research results, models, and experiences associated with the complexity of behavioural decision processes and socio‐economic phenomena. In 2018, DECON was held at Campus Tecnológico de la Fábrica de Armas, University of Castilla-La Mancha, Toledo, Spain, as part of the 15th International Conference on Distributed Computing and Artificial Intelligence. For the third consecutive year, this book have drawn inspiration from Herbert A. Simon’s interdisciplinary legacy and, in particular, is devoted to designs, models, and techniques for boundedly rational decisions, involving several fields of study and expertise. It is worth noting that the recognition of relevant decision‐making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business management, operations, and production. Therefore, decision‐making issues are of fundamental importance in all branches of economics addressed with different methodological approaches. As a matter of fact, the study of decision‐making has become the focus of intense research efforts, both theoretical and applied, forming a veritable bridge between theory and practice as well as science and business organisations, whose pillars are based on insightful cutting‐edge experimental, behavioural, and computational approaches on the one hand, and celebrating the value of science as well as the close relationship between economics and complexity on the other. In this respect, the international scientific community acknowledges Herbert A. Simon’s research endeavours to understand the processes involved in economic decision‐making and their implications for the advancement of economic professions. Within the field of decision‐making, indeed, Simon has become a mainstay of bounded rationality and satisficing. His rejection of the standard (unrealistic) decision‐making models adopted by neoclassical economists inspired social scientists worldwide with the purpose to develop research programmes aimed at studying decision‐making empirically, experimentally, and computationally. The main achievements concern decision‐making for individuals, firms, markets, governments, institutions, and, last but not least, science and research. This book of selected papers tackles these issues that Simon broached in a professional career spanning more than sixty years. The Editors of this book dedicated it to Herb.
Decision Economics: Minds, Machines, and their Society (Studies in Computational Intelligence #990)
by Edgardo Bucciarelli Shu-Heng Chen Juan M. Corchado Javier Parra D.This book is the result of a multi-year research project led and sponsored by the University of Chieti-Pescara, National Chengchi University, University of Salamanca, and Osaka University. It is the fifth volume to emerge from that international project, held under the aegis of the United Nations Academic Impact in 2020. All the essays in this volume were (virtually) discussed at the University of L’Aquila―as the venue of the 2nd International Conference on Decision Economics, a three-day global gathering of approximately one hundred scholars and practitioners—and were subjected to thorough peer review by leading experts in the field. The essays reflect the extent, diversity, and richness of several research areas, both normative and descriptive, and are an invaluable resource for graduate-level and PhD students, academics, researchers, policymakers and other professionals, especially in the social and cognitive sciences. Given its interdisciplinary scope, the book subsequently delivers new approaches on how to contribute to the future of economics, providing alternative explanations for various socio-economic issues such as computable humanities; cognitive, behavioural, and experimental perspectives in economics; data analysis and machine learning as well as research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics; agent-based modelling and the related. The editors are grateful to the scientific committee for its continuous support throughout the research project as well as to the many participants for their insightful comments and always probing questions. In any case, the collaboration involved in the project extends far beyond the group of authors published in this volume and is reflected in the quality of the essays published over the years.
Decision Forests for Computer Vision and Medical Image Analysis
by Antonio Criminisi J ShottonThis practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.
Decision Intelligence: Proceedings of the International Conference on Information Technology, InCITe 2023, Volume 1 (Lecture Notes in Electrical Engineering #1079)
by B. K. Murthy B. V. R. Reddy Nitasha Hasteer Jean-Paul Van BelleThis 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.
Decision Intelligence: Human–Machine Integration for Decision-Making
by Miriam O'CallaghanRevealing the limitations of human decision-making, this book explores how Artificial Intelligence (AI) can be used to optimize decisions for improved business outcomes and efficiency, as well as looking ahead to the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise. From the theories and concepts used to design autonomous intelligent agents to the technologies that power DI systems and the ways in which companies use decision-making building blocks to build DI solutions that enable businesses to democratize AI, this book presents an impressive framework to integrate artificial and human intelligence for the success of different types of business decisions. Replete with case studies on DI applications, as well as wider discussions on the social implications of the technology, Decision Intelligence: Human–Machine Integration for Decision Making appeals to both students of AI and data sciences and businesses considering DI adoption.
Decision Intelligence Analytics and the Implementation of Strategic Business Management (EAI/Springer Innovations in Communication and Computing)
by Dieu Hack-Polay Tanupriya Choudhury P. Mary Jeyanthi T P Singh Sheikh AbujarThis 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.
Decision Intelligence For Dummies
by Pamela BakerLearn 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.