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future decision-makers in the field of health information systems. Users will find sections on the question of reusing data for other purposes;
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agricultural production across all countries and continents for the years 1989-2000. The data are disseminated to serve the needs of scholars;
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This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of Data Science for Social;
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than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners;
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, but, until now, the patterns discovered from data have not always been 'actionable' for decision-makers in Socio-Technical Organizations (STO;
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Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with;
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Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with;
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The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for;
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The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for;
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to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling;
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excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants;
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higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data;
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An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision;
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An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision;
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Evidence-Based Decision-Making: How to Leverage Available Data and Avoid Cognitive Biases examines how a wide range of factual evidence;
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rely on data provided by insurance companies, consultants, research firms, and the federal government to help them make a host of decisions;
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This book constitutes the refereed proceedings of the 16th International Conference on Modeling Decisions for Artificial Intelligence, MDAI;
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provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a;
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perspectives on how big data and business analytics are increasingly essential in better decision making. This edited work explores the;
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and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data;
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This book contains international perspectives that unifies the themes of strategic management, decision theory, and data science. It;
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decisions to reinvent a business. Equally important all decision makers must learn to ask the right questions, use data and computer support;
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Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy;
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Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy;
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as a guide to data-based decision making. The Handbook of Data-Based Decision Making in Education is a must read for researchers who are;
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