Applied Big Data Analytics In Operations Management
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Applied Big Data Analytics In Operations Management
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Author : Kumar, Manish
language : en
Publisher: IGI Global
Release Date : 2016-09-30
Applied Big Data Analytics In Operations Management written by Kumar, Manish and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Business & Economics categories.
Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.
Big Data Analytics In Supply Chain Management
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Author : Iman Rahimi
language : en
Publisher: CRC Press
Release Date : 2020-12-20
Big Data Analytics In Supply Chain Management written by Iman Rahimi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-20 with Computers categories.
In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.
Operations Management And Data Analytics Modelling
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Author : Lalit Kumar Awasthi
language : en
Publisher: CRC Press
Release Date : 2021-12-30
Operations Management And Data Analytics Modelling written by Lalit Kumar Awasthi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-30 with Technology & Engineering categories.
Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0. It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma. Features Discusses the importance of data analytics in industrial operations to improve economy Provides step-by-step implementation of operation management models to identify best practices Covers in-depth analysis using data-based operation management tools and techniques Discusses mathematical modelling for novel operation management models to solve industrial problems This book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science.
Management Decision Making Big Data And Analytics
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Author : Simone Gressel
language : en
Publisher: SAGE
Release Date : 2020-10-12
Management Decision Making Big Data And Analytics written by Simone Gressel and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-12 with Business & Economics categories.
An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
Big Data Analytics In Supply Chain Management
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Author : Iman Rahimi
language : en
Publisher: CRC Press
Release Date : 2020-12-20
Big Data Analytics In Supply Chain Management written by Iman Rahimi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-20 with Computers categories.
In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.
Applied Business Analytics
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Author : Nathaniel Lin
language : en
Publisher: FT Press
Release Date : 2014-12-12
Applied Business Analytics written by Nathaniel Lin and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-12 with Business & Economics categories.
Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll discover why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics... how to become one of those deciders... and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification.
The Applied Business Analytics Casebook
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Author : Matthew J. Drake
language : en
Publisher: FT Press
Release Date : 2013-10-09
The Applied Business Analytics Casebook written by Matthew J. Drake and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-09 with Business & Economics categories.
The first collection of cases on “big data” analytics for supply chain, operations research, and operations management, this reference puts readers in the position of the analytics professional and decision-maker. Perfect for students, practitioners, and certification candidates in SCM, OM, and OR, these short, focused, to-the-point case studies illustrate the entire decision-making process. They provide realistic opportunities to perform analyses, interpret output, and recommend an optimal course of action. Contributed by leading “big data” experts, the cases in The Applied Business Analytics Casebook covers: Forecasting and statistical analysis: time series forecasting models, regression models, data visualization, and hypothesis testing Optimization and simulation: linear, integer, and nonlinear programming; Monte Carlo simulation and risk analysis; and stochastic optimization Decision analysis: decision making under uncertainty; expected value of perfect information; decision trees; game theory models; AHP; and multi-criteria decision making Advanced business analytics: data warehousing/mining; text mining; neural networks; financial analytics; CRM analytics; and revenue management models
Applied Big Data Analytics And Its Role In Covid 19 Research
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Author : Zhao, Peng
language : en
Publisher: IGI Global
Release Date : 2022-04-29
Applied Big Data Analytics And Its Role In Covid 19 Research written by Zhao, Peng and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-29 with Computers categories.
There has been a multitude of studies focused on the COVID-19 pandemic across fields and disciplines as all sectors of life have had to adjust the way things are done and adapt to the constantly shifting environment. These studies are crucial as they provide support and perspectives on how things are changing and what needs to be done to stay afloat. Connecting COVID-19-related studies and big data analytics is crucial for the advancement of industrial applications and research areas. Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics. Featuring coverage on a broad range of big data technologies such as data gathering, artificial intelligence, smart diagnostics, and mining mobility, this publication provides concrete examples and cases of usage of data-driven projects in COVID-19 research. This reference work is a vital resource for data scientists, technical managers, researchers, scholars, practitioners, academicians, instructors, and students.
Big Data For The Greater Good
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Author : Ali Emrouznejad
language : en
Publisher: Springer
Release Date : 2018-07-13
Big Data For The Greater Good written by Ali Emrouznejad and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-13 with Technology & Engineering categories.
This book highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks – many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes.
Business Intelligence Strategy And Big Data Analytics
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Author : Steve Williams
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-04-08
Business Intelligence Strategy And Big Data Analytics written by Steve Williams and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-08 with Computers categories.
Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like “big data” and “big data analytics” have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. Provides ideas for improving the business performance of one’s company or business functions Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans