Data and Decision Sciences in Action

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Author :
Publisher : Springer
ISBN 13 : 3319559141
Total Pages : 414 pages
Book Rating : 4.48/5 ( download)

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Book Synopsis Data and Decision Sciences in Action by : Ruhul Sarker

Download or read book Data and Decision Sciences in Action written by Ruhul Sarker and published by Springer. This book was released on 2017-07-26 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a concise and multidisciplinary reference guide to the state of the art in Australian operations research, this book will be of great value to academics working in many disciplines associated with operations research, as well as industrial practitioners engaged in planning, scheduling and logistics. Over 60 papers, with topics ranging from academic research techniques and case studies to industrial and administrative best practices in operations research, address aspects such as: • optimization, combinatorial optimization, decision analysis, supply-chain management, queuing and routing, and project management; and • logistics, government, cyber security, health-care systems, mining and material processing, ergonomics and human factors, space applications, telecommunications and transportation, among many others. This book presents the Proceedings of the National Conference of the Australian Society for Operations Research, the premier professional organization for Australian academics and practitioners working in optimization and other disciplines related to operations research. The conference was held in Canberra in November 2016.

Data and Decision Sciences in Action 2

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Author :
Publisher : Springer Nature
ISBN 13 : 3030601358
Total Pages : 310 pages
Book Rating : 4.55/5 ( download)

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Book Synopsis Data and Decision Sciences in Action 2 by : Andreas T. Ernst

Download or read book Data and Decision Sciences in Action 2 written by Andreas T. Ernst and published by Springer Nature. This book was released on 2021-02-26 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Joint 2018 National Conferences of the Australian Society for Operations Research (ASOR) and the Defence Operations Research Symposium (DORS). Offering a fascinating insight into the state of the art in Australian operations research, this book is of great interest to academics and other professional researchers working in operations research and analytics, as well as practitioners addressing strategic planning, operations management, and other data-driven decision-making challenges in the domains of commerce, industry, defence, the environment, humanitarianism, and agriculture. The book comprises 21 papers on topics ranging from methodological advances to case studies, and addresses application domains including supply chains, government services, defence, cybersecurity, healthcare, mining and material processing, agriculture, natural hazards, telecommunications and transportation. ASOR is the premier professional organization for Australian academics and practitioners working in optimization and other disciplines related to operations research. The conference was held in Melbourne, Australia, in December 2018.

Data and Decision Sciences - Recent Advances and Applications

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Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1803562870
Total Pages : 132 pages
Book Rating : 4.72/5 ( download)

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Book Synopsis Data and Decision Sciences - Recent Advances and Applications by :

Download or read book Data and Decision Sciences - Recent Advances and Applications written by and published by BoD – Books on Demand. This book was released on 2023-10-25 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of Data and Decision Sciences (DDS) and recent advances and applications in space-based systems and business, medical, and agriculture processes, decision optimization modeling, and cognitive decision-making. Written by experts, this volume is organized into four sections and seven chapters. It is a valuable resource for educators, engineers, scientists, and researchers in the field of DDS.

Emerging Trends in Decision Sciences and Business Operations

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Author :
Publisher : Taylor & Francis
ISBN 13 : 1000641414
Total Pages : 296 pages
Book Rating : 4.17/5 ( download)

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Book Synopsis Emerging Trends in Decision Sciences and Business Operations by : Avinash K Shrivastava

Download or read book Emerging Trends in Decision Sciences and Business Operations written by Avinash K Shrivastava and published by Taylor & Francis. This book was released on 2022-08-29 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume analyses the rising inclusion of new and emerging technologies in business. It measures the effectiveness and challenges of these tools in various aspects of strategy and decision making within small and big businesses. Businesses in the competitive market must be agile and innovative to drive growth and the inclusion of technology and reliance on data science for decision-making is fraught with its own set of challenges. Through various case studies and analysis of trends, the book explores diverse dimensions of decision science from a micro as well as macro perspective. It examines the function, management and implementation of new technologies, like big data and AI in business operations and infrastructure highlighting their practical applications as well as the barriers to their adoption. This book will be useful to scholars and researchers of management studies, business management, financial management, business economics, international business, finance and marketing, development studies and economics. It will also interest policymakers and practitioners in the field.

Optimizing Data-to-Learning-to-Action

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Publisher : Apress
ISBN 13 : 1484235312
Total Pages : 201 pages
Book Rating : 4.17/5 ( download)

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Book Synopsis Optimizing Data-to-Learning-to-Action by : Steven Flinn

Download or read book Optimizing Data-to-Learning-to-Action written by Steven Flinn and published by Apress. This book was released on 2018-04-06 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply a powerful new approach and method that ensures continuous performance improvement for your business. You will learn how to determine and value the people, process, and technology-based solutions that will optimize your organization’s data-to-learning-to-action processes. This book describes in detail how to holistically optimize the chain of activities that span from data to learning to decisions to actions, an imperative for achieving outstanding performance in today’s business environment. Adapting and integrating insights from decision science, constraint theory, and process improvement, the book provides a method that is clear, effective, and can be applied to nearly every business function and sector. You will learn how to systematically work backwards from decisions to data, estimate the flow of value along the chain, and identify the inevitable value bottlenecks. And, importantly, you will learn techniques for quantifying the value that can be attained by successfully addressing the bottlenecks, providing the credible support needed to make the right level of investments at the right place and at just the right time. In today’s dynamic environment, with its never-ending stream of new, disruptive technologies that executives must consider (e.g., cloud computing, Internet of Things, AI/machine learning, business intelligence, enterprise social, etc., along with the associated big data generated), author Steven Flinn provides the comprehensive approach that is needed for making effective decisions about these technologies, underpinned by credibly quantified value. What You’ll Learn Understand data-to-learning-to-action processes and their fundamental elements Discover the highest leverage data-to-learning-to-action processes in your organization Identify the key decisions that are associated with a data-to-learning-to-action process Know why it’s NOT all about data, but it IS all about decisions and learning Determine the value upside of enhanced learning that can improve decisions Work backwards from the decisions to determine the value constraints in data-to-learning-to-action processes Evaluate people, process, and technology-based solution options to address the constraints Quantify the expected value of each of the solution options and prioritize accordingly Implement, measure, and continuously improve by addressing the next constraints on value Who This Book Is For Business executives and managers seeking the next level of organizational performance, knowledge workers who want to maximize their impact, technology managers and practitioners who require a more effective means to prioritize technology options and deployments, technology providers who need a way to credibly quantify the value of their offerings, and consultants who are ready to build practices around the next big business performance paradigm

Process Mining

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Publisher : Springer
ISBN 13 : 3662498510
Total Pages : 477 pages
Book Rating : 4.14/5 ( download)

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Book Synopsis Process Mining by : Wil M. P. van der Aalst

Download or read book Process Mining written by Wil M. P. van der Aalst and published by Springer. This book was released on 2016-04-15 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.

The Best Thinking in Business Analytics from the Decision Sciences Institute

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Author :
Publisher : FT Press
ISBN 13 : 0134073053
Total Pages : 454 pages
Book Rating : 4.57/5 ( download)

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Book Synopsis The Best Thinking in Business Analytics from the Decision Sciences Institute by : Decision Sciences Institute

Download or read book The Best Thinking in Business Analytics from the Decision Sciences Institute written by Decision Sciences Institute and published by FT Press. This book was released on 2015-08-18 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, business success depends on making great decisions – and making them fast. Leading organizations apply sophisticated business analytics tools and technologies to evaluate vast amounts of data, glean new insights, and increase both the speed and quality of decision making. In The Best Thinking and Practices in Business Analytics from the Decision Sciences Institute, DSI has compiled award-winning and award-nominated contributions from its most recent conferences: papers that illuminate exceptionally high-value applications and research on analytics for decision-making. These papers have appeared in no other DSI collection. Explore them here, and you’ll discover powerful new opportunities for competitive advantage through analytics. For all business, academic, and organizational professionals concerned with the science of more effective decision-making; and for undergraduate students, graduate students, and certification candidates in all related fields.

Analytical Skills for AI and Data Science

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Publisher : O'Reilly Media
ISBN 13 : 1492060917
Total Pages : 244 pages
Book Rating : 4.18/5 ( download)

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Book Synopsis Analytical Skills for AI and Data Science by : Daniel Vaughan

Download or read book Analytical Skills for AI and Data Science written by Daniel Vaughan and published by O'Reilly Media. This book was released on 2020-05-21 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs. Author Daniel Vaughan shows data scientists, analytics practitioners, and others interested in using AI to transform their businesses not only how to ask the right questions but also how to generate value using modern AI technologies and decision-making principles. You’ll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. Break business decisions into stages that can be tackled using different skills from the analytical toolbox Identify and embrace uncertainty in decision making and protect against common human biases Customize optimal decisions to different customers using predictive and prescriptive methods and technologies Ask business questions that create high value through AI- and data-driven technologies

Proceedings of the Fourth International Forum on Decision Sciences

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Publisher : Springer
ISBN 13 : 9811029202
Total Pages : 899 pages
Book Rating : 4.02/5 ( download)

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Book Synopsis Proceedings of the Fourth International Forum on Decision Sciences by : Xiang Li

Download or read book Proceedings of the Fourth International Forum on Decision Sciences written by Xiang Li and published by Springer. This book was released on 2017-01-22 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: These conference proceedings focus on the topics of data-driven decision-making, stochastic decision-making, fuzzy decision-making and their applications in real-life problems. Beijing University of Chemical Technology organized IFDS2016, the 4th International Forum on Decision Sciences, with the theme “Data-Driven Decision-Making.” The proceedings collect 84 selected papers presenting cutting-edge modeling and solution methods and include numerous practical case studies, making it a valuable resource for students, researchers and practitioners working in the fields of decision science, operations research, management science and engineering.

Machine Learning for Decision Sciences with Case Studies in Python

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Author :
Publisher : CRC Press
ISBN 13 : 1000590933
Total Pages : 476 pages
Book Rating : 4.37/5 ( download)

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Book Synopsis Machine Learning for Decision Sciences with Case Studies in Python by : S. Sumathi

Download or read book Machine Learning for Decision Sciences with Case Studies in Python written by S. Sumathi and published by CRC Press. This book was released on 2022-07-06 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data. Features: Explains the basic concepts of Python and its role in machine learning. Provides comprehensive coverage of feature engineering including real-time case studies. Perceives the structural patterns with reference to data science and statistics and analytics. Includes machine learning-based structured exercises. Appreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learning. This book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering.