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Ecology, Biodiversity and Conservation: With Applications in R (Ecology, Biodiversity and Conservation)
by Antoine Guisan Wilfried Thuiller Di Cola Valeria Damien Georges Zimmermann Niklaus E. Psomas Achilleas Niklaus E. Achilleas PsomasThis book introduces the key stages of niche-based habitat suitability model building, evaluation and prediction required for understanding and predicting future patterns of species and biodiversity. Beginning with the main theory behind ecological niches and species distributions, the book proceeds through all major steps of model building, from conceptualization and model training to model evaluation and spatio-temporal predictions. Extensive examples using R support graduate students and researchers in quantifying ecological niches and predicting species distributions with their own data, and help to address key environmental and conservation problems. Reflecting this highly active field of research, the book incorporates the latest developments from informatics and statistics, as well as using data from remote sources such as satellite imagery. A website at www. unil. ch/hsdm contains the codes and supporting material required to run the examples and teach courses.
eCommerce Economics, Second Edition
by David VanHooseThis second edition of eCommerce Economics addresses the economic issues associated with using computer-mediated electronic networks, such as the Internet, as mechanisms for transferring ownership of or rights to use goods and services. After studying this book, students will recognize problems that arise in the electronic marketplace, such as how to gauge the competitive environment, what products to offer, how to market those products, and how to price those products. They also will understand the conceptual tools required to evaluate the proper scope of public policies relating to electronic commerce. Core topics covered in the book include the underpinning of electronic commerce and the application of basic economic principles, including the theories of perfect and imperfect competition, to the electronic marketplace. Building on this foundation, the book discusses virtual products, network industries, and business strategies and conduct. Additional key topics include Internet advertising, intellectual property rights in a digital environment, regulatory issues in electronic markets, public sector issues, online banking and finance, digital cash, international electronic trade, and the implications of e-commerce for aggregate economic activity.
eCommerce in the Cloud
by Kelly GoetschIs your eCommerce solution ready for the cloud? This practical guide shows experienced and aspiring web architects alike how to adopt cloud computing incrementally, using public Infrastructure-as-a-Service and Platform-as-a-Service. You will learn how to marshal as much capacity as you need to handle peak holiday or special-event traffic.Written by eCommerce expert Kelly Goetsch, this book helps architects leverage recent technological advances that have made it possible to run an entire enterprise-level eCommerce platform from a cloud.Explore cloud service models: Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-ServiceLearn about public, hybrid, and private cloud deployment modelsUnderstand the impact of omnichannel retailing on platform and deployment architecturesBuild an auto-scaling solution that can quickly add or subtract hardware in response to real-time trafficRe-apply what you already know about security to the cloudRun a single eCommerce platform from multiple data centers, including several forms of multi-masterBuild a hybrid solution or deploy your entire platform to the cloudLearn application and deployment architecture for "cloud native" through legacy eCommerce platformsUse Software-as-a-Service for eCommerce, including Content Delivery Networks and Global Site Load Balancing services
eCommerce In A Week: Selling Online In Seven Simple Steps
by Nick SmithIn today's working environment, which is changing faster than ever, e-commerce is more than a buzzword. It is a vital skill to help you survive and get ahead in your career. Digital marketing consultant Nick Smith has been there and done it, and in this short, accessible book he shares a lifetime of hard-earned wisdom and practical advice.Sunday: Getting ready to start your storeMonday: Basic e-commerce setupTuesday: Social marketing for e-commerceWednesday: Pay-per-click (PPC) marketing for e-commerceThursday: Search engine optimization (SEO) for e-commerceFriday: Customer service for e-commerceSaturday: Bringing it all together into the ultimate e-commerce marketing system
eCommerce klipp & klar (WiWi klipp & klar)
by Jan-Frederik Engelhardt Alexander MagerhansDieses Lehrbuch präsentiert eine Einführung und Vertiefung der wesentlichen Themenfelder des eCommerce. Der Fokus liegt dabei auf kundenzentrierten Aspekten, wie z.B. der Kundenzufriedenheit und -erwartung. Diese werden entlang einer Customer Journey systematisiert und ausgeführt. Neben Themen wie dem Kundenmanagement wird vor allem auch auf Onlineshops im eCommerce, insbesondere auf deren Gestaltungsmöglichkeiten, eingegangen. Dabei wird aufgezeigt, wie eine logische Wertschöpfung nach Gesetzen der Netzökonomie aussehen kann. Schließlich zeigen die Autoren die Erfolgsfaktoren des eCommerce auf, für die die bestmögliche Kenntnis des Kunden eine wesentliche Grundlage bildet. Das praxisorientierte Buch richtet sich an Studierende und auch Praktiker, die den eCommerce in Ihrem Unternehmen aktiv gestalten und entwickeln.
Ecommerce Reimagined: Retail and Ecommerce in China
by Sharon GaiThis book offers a practical guide to Chinese ecommerce markets for businesspeople and scholars. China represents a $5.6 trillion retail market, with the highest ecommerce penetration rate in the world. Due to the COVID-19 pandemic, brands are investing more in growing online sales. Written from the heart of the world’s largest e-commerce platform, Ecommerce Reimagined: Retail and Ecommerce in China is a book that aims to satisfy the growing need of entrepreneurs and businesses hoping to tap into China’s market and provide context to students and academics who post an interest in learning about how ecommerce has shaped the Chinese retail space.
Econometric Analysis of Carbon Markets: The European Union Emissions Trading Scheme and the Clean Development Mechanism
by Julien ChevallierThrough analysis of the European Union Emissions Trading Scheme (EU ETS) and the Clean Development Mechanism (CDM), this book demonstrates how to use a variety of econometric techniques to analyze the evolving and expanding carbon markets sphere, techniques that can be extrapolated to the worldwide marketplace. It features stylized facts about carbon markets from an economics perspective, as well as covering key aspects of pricing strategies, risk and portfolio management.
Econometrics and Data Science: Apply Data Science Techniques to Model Complex Problems and Implement Solutions for Economic Problems
by Tshepo Chris NokeriGet up to speed on the application of machine learning approaches in macroeconomic research. This book brings together economics and data science.Author Tshepo Chris Nokeri begins by introducing you to covariance analysis, correlation analysis, cross-validation, hyperparameter optimization, regression analysis, and residual analysis. In addition, he presents an approach to contend with multi-collinearity. He then debunks a time series model recognized as the additive model. He reveals a technique for binarizing an economic feature to perform classification analysis using logistic regression. He brings in the Hidden Markov Model, used to discover hidden patterns and growth in the world economy. The author demonstrates unsupervised machine learning techniques such as principal component analysis and cluster analysis. Key deep learning concepts and ways of structuring artificial neural networks are explored along with training them and assessing their performance. The Monte Carlo simulation technique is applied to stimulate the purchasing power of money in an economy. Lastly, the Structural Equation Model (SEM) is considered to integrate correlation analysis, factor analysis, multivariate analysis, causal analysis, and path analysis.After reading this book, you should be able to recognize the connection between econometrics and data science. You will know how to apply a machine learning approach to modeling complex economic problems and others beyond this book. You will know how to circumvent and enhance model performance, together with the practical implications of a machine learning approach in econometrics, and you will be able to deal with pressing economic problems. What You Will LearnExamine complex, multivariate, linear-causal structures through the path and structural analysis technique, including non-linearity and hidden statesBe familiar with practical applications of machine learning and deep learning in econometricsUnderstand theoretical framework and hypothesis development, and techniques for selecting appropriate modelsDevelop, test, validate, and improve key supervised (i.e., regression and classification) and unsupervised (i.e., dimension reduction and cluster analysis) machine learning models, alongside neural networks, Markov, and SEM modelsRepresent and interpret data and models Who This Book Is ForBeginning and intermediate data scientists, economists, machine learning engineers, statisticians, and business executives
Econometrics of Risk
by Van-Nam Huynh Vladik Kreinovich Songsak Sriboonchitta Komsan SuriyaThis edited book contains several state-of-the-art papers devoted to econometrics of risk. Some papers provide theoretical analysis of the corresponding mathematical, statistical, computational, and economical models. Other papers describe applications of the novel risk-related econometric techniques to real-life economic situations. The book presents new methods developed just recently, in particular, methods using non-Gaussian heavy-tailed distributions, methods using non-Gaussian copulas to properly take into account dependence between different quantities, methods taking into account imprecise ("fuzzy") expert knowledge, and many other innovative techniques. This versatile volume helps practitioners to learn how to apply new techniques of econometrics of risk, and researchers to further improve the existing models and to come up with new ideas on how to best take into account economic risks.
Economic Analysis of the Digital Economy (National Bureau of Economic Research Conference Report)
by Catherine E. Tucker Avi Goldfarb Shane M. GreensteinAs the cost of storing, sharing, and analyzing data has decreased, economic activity has become increasingly digital. But while the effects of digital technology and improved digital communication have been explored in a variety of contexts, the impact on economic activity--from consumer and entrepreneurial behavior to the ways in which governments determine policy--is less well understood. Economic Analysis of the Digital Economy explores the economic impact of digitization, with each chapter identifying a promising new area of research. The Internet is one of the key drivers of growth in digital communication, and the first set of chapters discusses basic supply-and-demand factors related to access. Later chapters discuss new opportunities and challenges created by digital technology and describe some of the most pressing policy issues. As digital technologies continue to gain in momentum and importance, it has become clear that digitization has features that do not fit well into traditional economic models. This suggests a need for a better understanding of the impact of digital technology on economic activity, and Economic Analysis of the Digital Economy brings together leading scholars to explore this emerging area of research.
An Economic Analysis on Automated Construction Safety
by Rita Yi LiThis book addresses information technologies recently applied in the field of construction safety. Combining case studies, literature reviews and interviews to study the issue, it presents cutting-edge applications of various information technologies (ITs) in construction in different parts of the world, together with a wealth of figures, tables and examples. Though primarily intended for researchers and experts in the field, the book will also benefit graduate students.
Economic and Policy Implications of Artificial Intelligence (Studies in Systems, Decision and Control #288)
by Domenico Marino Melchiorre A. MonacaThis book presents original research articles addressing various aspects of artificial intelligence as applied to economics, law, management and optimization. The topics discussed include economics, policies, finance, law, resource allocation strategies and information technology. Combining the input of contributing professors and researchers from Italian and international universities, the book will be of interest to students, researchers and practitioners, as well as members of the general public interested in the economic and policy implications of artificial intelligence.
Economic Crime: From Conception to Response (Global Issues in Crime and Justice)
by Mark Button Branislav Hock David ShepherdThis book is the first attempt to establish 'economic crime' as a new sub-discipline within criminology. Fraud, corruption, bribery, money laundering, price-fixing cartels and intellectual property crimes pursued typically for financial and professional gain, have devastating consequences for the prosperity of economic life. While most police forces in the UK and the USA have an ‘economic crime’ department, and many European bodies such as Europol use the term and develop strategies and structures to deal with it, it is yet to grain traction as a widely used term in the academic community. Economic Crime: From Conception to Response aims to change that and covers: definitions of the key premises of economic crime as the academic sub-discipline within criminology; an overview of the key research on each of the crimes associated with economic crime; public, private and global responses to economic crime across its different forms and sectors of the economy, both within the UK and globally. This book is an essential resource for students, academics and practitioners engaged with aspects of economic crime, as well as the related areas of financial crime, white-collar crime and crimes of the powerful.
Economic Impact of Open Source on Small Business: A Case Study
by Roger Magoulas Mike Hendrickson Tim O'ReillyOpen source is not only a catalyst for small business growth, but also a driver of future success for many startups today. Bringing together Bluehost anonymized customer data and trends with O'Reilly Media's job market data, along with other sources of trend data, this report captures the current state of open source as it relates to small to medium-sized businesses.
Economic Modeling Using Artificial Intelligence Methods
by Tshilidzi MarwalaEconomic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networksradial basis functionssupport vector machinesrough setsgenetic algorithmparticle swarm optimizationsimulated annealingmulti-agent systemincremental learningfuzzy networksSignal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace - and vice versa - is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners.
Economic Models for Managing Cloud Services
by Hai Dong Athman Bouguettaya Sajib MistryThe authors introduce both the quantitative and qualitative economic models as optimization tools for the selection of long-term cloud service requests. The economic models fit almost intuitively in the way business is usually done and maximize the profit of a cloud provider for a long-term period. The authors propose a new multivariate Hidden Markov and Autoregressive Integrated Moving Average (HMM-ARIMA) model to predict various patterns of runtime resource utilization. A heuristic-based Integer Linear Programming (ILP) optimization approach is developed to maximize the runtime resource utilization. It deploys a Dynamic Bayesian Network (DBN) to model the dynamic pricing and long-term operating cost. A new Hybrid Adaptive Genetic Algorithm (HAGA) is proposed that optimizes a non-linear profit function periodically to address the stochastic arrival of requests. Next, the authors explore the Temporal Conditional Preference Network (TempCP-Net) as the qualitative economic model to represent the high-level IaaS business strategies. The temporal qualitative preferences are indexed in a multidimensional k-d tree to efficiently compute the preference ranking at runtime. A three-dimensional Q-learning approach is developed to find an optimal qualitative composition using statistical analysis on historical request patterns. Finally, the authors propose a new multivariate approach to predict future Quality of Service (QoS) performances of peer service providers to efficiently configure a TempCP-Net. It discusses the experimental results and evaluates the efficiency of the proposed composition framework using Google Cluster data, real-world QoS data, and synthetic data. It also explores the significance of the proposed approach in creating an economically viable and stable cloud market. This book can be utilized as a useful reference to anyone who is interested in theory, practice, and application of economic models in cloud computing. This book will be an invaluable guide for small and medium entrepreneurs who have invested or plan to invest in cloud infrastructures and services. Overall, this book is suitable for a wide audience that includes students, researchers, and practitioners studying or working in service-oriented computing and cloud computing.
The Economic Philosophy of the Internet of Things (Routledge Studies in the Economics of Innovation)
by James JuniperTo properly understand the nature of the digital economy we need to investigate the phenomenon of a "ubiquitous computing system" (UCS). As defined by Robin Milner, this notion implies the following characteristics: (i) it will continually make decisions hitherto made by us; (ii) it will be vast, maybe 100 times today’s systems; (iii) it must continually adapt, on-line, to new requirements; and, (iv) individual UCSs will interact with one another. This book argues that neoclassical approaches to modelling economic behaviour based on optimal control by "representative-agents" are ill-suited to a world typified by concurrency, decentralized control, and interaction. To this end, it argues for the development of new, process-based approaches to analysis, modelling, and simulation. The book provides the context—both philosophical and mathematical—for the construction and application of new, rigorous, and meaningful analytical tools. In terms of social theory, it adopts a Post-Cognitivist approach, the elements of which include the nature philosophy of Schelling, Marx’s critique of political economy, Peircean Pragmatism, Whitehead’s process philosophy, and Merleau-Ponty’s phenomenology of the flesh, along with cognitive scientific notions of embodied cognition and neural Darwinism, as well as more questionable notions of artificial intelligence that are encompassed by the rubric of "perception-and-action-without-intelligence".
Economic Systems Analysis: Statistical Indicators (Studies in Systems, Decision and Control #158)
by Innara R. Lyapina Lilia A. Mikheykina Lyudmila V. Oveshnikova Elena V. SibirskayaThis book explores a wide range of issues related to the methodology, organization, and technologies of analytical work, showing the potential of using analytical tools and statistical indicators for studying socio-economic processes, forecasting, organizing effective companies, and improving managerial decisions. At the level of “living knowledge” in the broad context, it describes the essence of analytical technologies and means of applying analytical and statistical work. The book is of interest to readers regardless of their specialization: scientific research, medicine, pedagogics, law, administrative work, or economic practice. Starting from the premise that readers are familiar with the theory of statistics, which has formulated the general methods and principles of establishing the quantitative characteristics of mass phenomena and processes, it describes the concepts, definitions, indicators and classifications of socio-economic statistics, taking into consideration the international standards and the present-day practice of statistics in Russia. Although concise, the book provides plenty of study material as well as questions at the end of each chapter It is particularly useful for those interested in self-study or remote education, as well as business leaders who are interested in gaining a scientific understanding of their financial and economic activities.
Economics and Social Conflict: Evil Actions and Evil Social Institutions in Virtual Worlds
by Carl D. MildenbergerThis book brings to life the classic thought experiment of a natural state. Provides data on the economic aspects of social conflict of 400.000 people living in a virtual anarchy; showing evil actions and rules exist from an economic perspective. Non-instrumental violence has economic effects and inciting people to fight are not overcome in time.
Economics and the Environment
by Peter van de PutHands-on guidance for programming the next generation of iOS apps If you want to create advanced level iOS apps that get noticed in the App Store, start with this expert book. Written by an international software developer and consultant who has delivered winning solutions for clients all over the world, this professional guide helps you build robust, professional iOS apps at a level that satisfies the demands of clients, companies, and your own creativity. The book includes full source code and invaluable insight from the author's extensive experience. Especially helpful are numerous case studies that shed light on key topics. Explores all topics necessary to help you build professional iOS applications perfectly targeted to clients' needs Covers essential topics including creating a professional UI, networking and data processing, integrating your app, and taking it into production Includes sample code and sample apps, ideal for hands-on learning Examines using social media aggregators, real-time currency converters, QR scanners, customer tracking and quality payment system Provides in-depth examples from the author's extensive career, as well as numerous case studies Take your programming skills to an advanced level with Professional iOS Programming.
The Economics of Artificial Intelligence: An Agenda (National Bureau of Economic Research Conference Report)
by Ajay Agrawal, Joshua Gans, and Avi GoldfarbAdvances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions. Contributors: Daron Acemoglu, Massachusetts Institute of Technology Philippe Aghion, Collège de France Ajay Agrawal, University of Toronto Susan Athey, Stanford University James Bessen, Boston University School of Law Erik Brynjolfsson, MIT Sloan School of Management Colin F. Camerer, California Institute of Technology Judith Chevalier, Yale School of Management Iain M. Cockburn, Boston University Tyler Cowen, George Mason University Jason Furman, Harvard Kennedy School Patrick Francois, University of British Columbia Alberto Galasso, University of Toronto Joshua Gans, University of Toronto Avi Goldfarb, University of Toronto Austan Goolsbee, University of Chicago Booth School of Business Rebecca Henderson, Harvard Business School Ginger Zhe Jin, University of Maryland Benjamin F. Jones, Northwestern University Charles I. Jones, Stanford University Daniel Kahneman, Princeton University Anton Korinek, Johns Hopkins University Mara Lederman, University of Toronto Hong Luo, Harvard Business School John McHale, National University of Ireland Paul R. Milgrom, Stanford University Matthew Mitchell, University of Toronto Alexander Oettl, Georgia Institute of Technology Andrea Prat, Columbia Business School Manav Raj, New York University Pascual Restrepo, Boston University Daniel Rock, MIT Sloan School of Management Jeffrey D. Sachs, Columbia University Robert Seamans, New York University Scott Stern, MIT Sloan School of Management Betsey Stevenson, University of Michigan Joseph E. Stiglitz. Columbia University Chad Syverson, University of Chicago Booth School of Business Matt Taddy, University of Chicago Booth School of Business Steven Tadelis, University of California, Berkeley Manuel Trajtenberg, Tel Aviv University Daniel Trefler, University of Toronto Catherine Tucker, MIT Sloan School of Management Hal Varian, University of California, Berkeley
The Economics of Artificial Intelligence: Health Care Challenges (National Bureau of Economic Research Conference Report)
by Ajay Agrawal, Joshua Gans, Avi Goldfarb, and Catherine E. TuckerA timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
The Economics of Big Science: Essays by Leading Scientists and Policymakers (Science Policy Reports)
by Hans Peter Beck Panagiotis CharitosThe essays in this open access volume identify the key ingredients for success in capitalizing on public investments in scientific projects and the development of large-scale research infrastructures.Investment in science – whether in education and training or through public funding for developing new research tools and technologies – is a crucial priority. Authors from big research laboratories/organizations, funding agencies and academia discuss how investing in science can produce societal benefits as well as identifying future challenges for scientists and policy makers. The volume cites different ways to assess the socio-economic impact of Research Infrastructures and their role as hubs of global collaboration, creativity and innovation. It highlights the different benefits stemming from fundamental research at the local, national and global level, while also inviting us to rethink the notion of “benefit” in the 21st century.Public investment is required to maintain the pace of technological and scientific advancements over the next decades. Far from advocating a radical transformation and massive expansion in funding, the authors suggest ways for maintaining a strong foundation of science and research to ensure that we continue to benefit from the outputs. The volume draws inspiration from the first “Economics of Big Science” workshop, held in Brussels in 2019 with the aim of creating a new space for dialogue and interaction between representatives of Big Science organizations, policy makers and academia. It aspires to provide useful reading for policy makers, scientists and students of science, who are increasingly called upon to explain the value of fundamental research and adopt the language and logic of economics when engaging in policy discussions.
The Economics of Blockchain Consensus: Exploring the Key Tradeoffs in Blockchain Design
by Joshua GansBlockchain technologies have been rapidly adopted for the creation of cryptocurrencies and have been explored for a myriad of applications. While this is of important economic interest, the computer science behind how blockchains operate to provide security and provenance has been largely inaccessible to economists. This book is a bridge between the computer science and the economics of blockchains. The focus is on the value and the achievement of blockchain consensus; that is, how distributed and independent nodes are able to reach an agreement on what the current state of digital ledgers, that are the product of blockchains, are. The book shows that the goals of computer scientists in designing blockchains place very high weight on security beyond what an economist trained in game theory and mechanism design would require. It shows how blockchains can be redesigned to account for key economic trade-offs, and will be of interest to researchers and students of economics, financial technology and computer science, alongside policymakers.
The Economics of Data, Analytics, and Digital Transformation: The theorems, laws, and empowerments to guide your organization's digital transformation
by Bill Schmarzo Dr. Kirk BorneBuild a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine LearningKey FeaturesMaster the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindsetAcquire implementable knowledge on digital transformation through 8 practical lawsExplore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctlyBook DescriptionIn today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator.The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise.The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning.By the end of the book, you will have the tools and techniques to drive your organization's digital transformation.Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book:Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon.What you will learnTrain your organization to transition from being data-driven to being value-drivenNavigate and master the big data business model maturity indexLearn a methodology for determining the economic value of your data and analyticsUnderstand how AI and machine learning can create analytics assets that appreciate in value the more that they are usedBecome aware of digital transformation misconceptions and pitfallsCreate empowered and dynamic teams that fuel your organization's digital transformationWho this book is forThis book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.