Data-driven decision-making for business, Grand Bang, Claus
Автор: Muenjohn Nuttawuth Название: Leadership ISBN: 1108459293 ISBN-13(EAN): 9781108459297 Издательство: Cambridge Academ Рейтинг: Цена: 11246.00 р. Наличие на складе: Поставка под заказ.
Описание: Leadership: Regional and Global Perspectives provides a fresh approach to leading in contemporary business environments. The text`s discussion of creativity, innovation, power, ethics and diversity provides students with a strong foundational knowledge and skills base, and supports them to become dynamic modern leaders.
Название: Data mining with decision trees: theory and applications ISBN: 9812771719 ISBN-13(EAN): 9789812771711 Издательство: World Scientific Publishing Рейтинг: Цена: 17424.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. Dedicated to the field of decision trees in data mining, this book covers various aspects of this technique.
Автор: Harnett Название: Data, Statistics and Decision Models with Excel ISBN: 0471133981 ISBN-13(EAN): 9780471133988 Издательство: Wiley Рейтинг: Цена: 41334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this text on statistical decision-making, the authors use examples such as computing values for the stock market, conducting market research reports or using an options pricing model to illuminate the subject matter.
Автор: Banasiewicz Название: Evidence-Based Decision-Making ISBN: 1138485292 ISBN-13(EAN): 9781138485297 Издательство: Taylor&Francis Рейтинг: Цена: 6123.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines how a wide range of factual evidence can be used to improve the quality of business decision-making, by helping decision makers circumvent various cognitive biases.
Автор: Banasiewicz Название: Evidence-Based Decision-Making ISBN: 1138485195 ISBN-13(EAN): 9781138485198 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines how a wide range of factual evidence can be used to improve the quality of business decision-making, by helping decision makers circumvent various cognitive biases.
Автор: Albright S. Christian, Winston Wayne L. Название: Business Analytics: Data Analysis & Decision Making ISBN: 0357109953 ISBN-13(EAN): 9780357109953 Издательство: Cengage Learning Рейтинг: Цена: 12670.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Master data analysis, modeling and the effective use of spreadsheets with the popular BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 7E. The quantitative methods approach in this edition helps you maximize your success with a proven teach-by-example presentation, inviting writing style and complete integration of the latest version of Excel. The approach is also compatible with earlier versions of Excel for your convenience.
This edition is more data-oriented than ever before with a new chapter on the two main Power BI tools in Excel -- Power Query and Power Pivot -- and a new section of data visualization with Tableau Public. Current problems and cases demonstrate the importance of the concepts you are learning. In addition, a useful Companion Website provides data and solutions files, SolverTable for optimization sensitivity analysis and Palisade DecisionTools Suite.
MindTap online resources are also available.
Автор: Surafel Luleseged Tilahun, Jean Medard T. Ngnotchouye Название: Optimization Techniques for Problem Solving in Uncertainty ISBN: 1522550917 ISBN-13(EAN): 9781522550914 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects.Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.
Companies have more data at their fingertips than ever before. Yet, studies show that most executives and organizations fail to extract real value from it. Challenging the conventional wisdom of data-driven decision-making, marketing professors and behavioral scientists Bart De Langhe and Stefano Puntoni argue that many analytics efforts flounder because data analyses are disconnected from the decisions to be made. In their important book, they offer a new approach they call decision-driven analytics. Counterintuitively, they argue that the key to making good decisions with data is to start by putting data in the background. Drawing from their own research and teaching, as well as real-world business cases, De Langhe and Puntoni offer four pillars of decision-driven analytics and guide you around common mistakes that have held back many organizations from using data for impact. In Decision-Driven Analytics, you will learn how to: + Avoid common pitfalls in data-driven decision-making; + Close the gap between managers and decision-making on one side, and data scientists and data analytics on the other; + Enhance the impact of data analytics on business outcomes; + Think without data to make better decisions; + Prepare for artificial intelligence’s impact on data analytics; and + Evaluate the costs and benefits of decision-driven analytics.
A must-read for anyone who wants to harness the power of data for competitive advantage, Decision-Driven Analytics will equip you with the skills and tools you need to more effectively use data for business outcomes and to make better decisions in today’s complex and data-rich world.
Companies have more data at their fingertips than ever before. Yet, studies show that most executives and organizations fail to extract real value from it. Challenging the conventional wisdom of data-driven decision-making, marketing professors and behavioral scientists Bart De Langhe and Stefano Puntoni argue that many analytics efforts flounder because data analyses are disconnected from the decisions to be made. In their important book, they offer a new approach they call decision-driven analytics. Counterintuitively, they argue that the key to making good decisions with data is to start by putting data in the background. Drawing from their own research and teaching, as well as real-world business cases, De Langhe and Puntoni offer four pillars of decision-driven analytics and guide you around common mistakes that have held back many organizations from using data for impact. In Decision-Driven Analytics, you will learn how to: + Avoid common pitfalls in data-driven decision-making; + Close the gap between managers and decision-making on one side, and data scientists and data analytics on the other; + Enhance the impact of data analytics on business outcomes; + Think without data to make better decisions; + Prepare for artificial intelligence’s impact on data analytics; and + Evaluate the costs and benefits of decision-driven analytics.
A must-read for anyone who wants to harness the power of data for competitive advantage, Decision-Driven Analytics will equip you with the skills and tools you need to more effectively use data for business outcomes and to make better decisions in today’s complex and data-rich world.
Автор: Mandl Название: Procurement Analytics ISBN: 3031432800 ISBN-13(EAN): 9783031432804 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This unique textbook explicitly addresses the intersection of advanced analytics and procurement. It is motivated by one core question: How can firms generate (economic) value from procurement data? It demonstrates that procurement is one of the major functions within a firm where data analytics, artificial intelligence, and operations research can successfully be leveraged to reduce cost and risk and to achieve resilience and sustainability goals. The book provides a methods-based overview of data-driven optimization of purchasing decisions. Besides presenting key concepts and applications, it particularly focuses on implementation, so as to help (future) procurement managers and data scientists quickly evaluate the value generated by a given data-driven solution. What sets this textbook apart is its combination of rigorous, state-of-the-art methodologies from academic research and first-hand experience from various application-oriented consulting projects in a range of industries. Though primarily intended for graduate students with a major in procurement and supply chain management, the book will also benefit purchasing managers with and without specific knowledge of advanced analytics techniques, and data scientists with and without specific experience in procurement.
Автор: Tovstiga Название: Strategy Praxis ISBN: 3031406915 ISBN-13(EAN): 9783031406911 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces a different approach to thinking about and engaging with strategy in the practice field. The insight-driven, first principles-based approach to strategising and strategic problem-solving developed in this book provides a conceptually rigorous yet pragmatic approach to strategising, and as such the book addresses deficiencies of the current theory-practice gap in the strategy field. In particular, the author introduces and develops a conceptually rigorous approach to the crucial transition stage from strategic analysis to strategic option formation in the strategy process. The book introduces several new concepts such as the firm's unique competing space and its strategic boundaries, the strategic thinking algorithm, and shows how these, when integrated with existing approaches and first-principles thinking, significantly enhance the coherence and effectiveness of strategic problem-solving in practice. Additionally, the book includes supplementary enhancing features throughout the chapters in the form of Praxis Reflections, Praxis Perspectives, and Praxis Cases that tie the concepts and methods presented to real-world strategy practice. This book will appeal not only to strategy practitioners, but also academic researchers and graduate-level students of strategic management.
Автор: Parul Gandhi; Surbhi Bhatia; Kapil Dev; Название: Data driven decision making using analytics ISBN: 1032058277 ISBN-13(EAN): 9781032058276 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining.Features:Covers descriptive statistics with respect to predictive analytics and business analytics.Discusses different data analytics platforms for real-time applications.Explain SMART business models.Includes algorithms in data sciences alongwith automated methods and models.Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics.This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.
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