Big Data Quantification For Complex Decision Making
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Big Data Quantification For Complex Decision Making
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Author : Zhang, Chao
language : en
Publisher: IGI Global
Release Date : 2024-04-16
Big Data Quantification For Complex Decision Making written by Zhang, Chao and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-16 with Business & Economics categories.
Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decision-Making tackles this challenge head-on, offering a comprehensive exploration of the tools necessary to distill valuable insights from datasets. This book serves as a tool for professionals, researchers, and students, empowering them to not only comprehend the significance of big data in decision-making but also to translate this understanding into real-world decision making. The central objective of the book is to examine the relationship between big data and decision-making. It strives to address multiple objectives, including understanding the intricacies of big data in decision-making, navigating methodological nuances, managing uncertainty adeptly, and bridging theoretical foundations with real-world applications. The book's core aspiration is to provide readers with a comprehensive toolbox, seamlessly integrating theoretical frameworks, practical applications, and forward-thinking perspectives. This equips readers with the means to effectively navigate the data-rich landscape of modern decision-making, fostering a heightened comprehension of strategic big data utilization. Tailored for a diverse audience, this book caters to researchers and academics in data science, decision science, machine learning, artificial intelligence, and related domains.
Effective Big Data Management And Opportunities For Implementation
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Author : Singh, Manoj Kumar
language : en
Publisher: IGI Global
Release Date : 2016-06-20
Effective Big Data Management And Opportunities For Implementation written by Singh, Manoj Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-20 with Computers categories.
“Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data.
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.
Analysis Of Large And Complex Data
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Author : Adalbert F.X. Wilhelm
language : en
Publisher: Springer
Release Date : 2016-08-03
Analysis Of Large And Complex Data written by Adalbert F.X. Wilhelm and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-03 with Computers categories.
This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.
Proceedings Of The 5th International Conference On Big Data Analytics For Cyber Physical System In Smart City Volume 1
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Author : Mohammed Atiquzzaman
language : en
Publisher: Springer Nature
Release Date : 2025-02-01
Proceedings Of The 5th International Conference On Big Data Analytics For Cyber Physical System In Smart City Volume 1 written by Mohammed Atiquzzaman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-01 with Computers categories.
This book gathers a selection of peer-reviewed papers presented at the 5th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2023) conference, held in Fuyang, China, on December 28–29. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
Proceeding Of The 2024 International Conference On Diversified Education And Social Development Desd 2024
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Author : Muhammad Raheel Mohyuddin
language : en
Publisher: Springer Nature
Release Date : 2024-12-27
Proceeding Of The 2024 International Conference On Diversified Education And Social Development Desd 2024 written by Muhammad Raheel Mohyuddin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Education categories.
This is an open access book. The 2024 International Conference on Diversified Education and Social Development [DESD2024] will be held on November 8th-10th, 2024 in Nanjing, Jiangsu, China. DESD2024 will provide an excellent international Academic forum for sharing knowledge and results in theory, methodology and applications of Diversified Education and Social Development. The conference looks for significant contributions to all major fields of Education and Social Development in theoretical and Application aspects. The aim of the conference is to provide a platform to the global researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
Computational Intelligence For Big Data Analysis
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Author : D.P. Acharjya
language : en
Publisher: Springer
Release Date : 2015-04-21
Computational Intelligence For Big Data Analysis written by D.P. Acharjya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-21 with Technology & Engineering categories.
The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.
Data Enabled Analytics
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Author : Joe Zhu
language : en
Publisher: Springer
Release Date : 2022-12-18
Data Enabled Analytics written by Joe Zhu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-18 with Business & Economics categories.
This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.
The Enterprise Big Data Framework
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Author : Jan-Willem Middelburg
language : en
Publisher: Kogan Page Publishers
Release Date : 2023-11-03
The Enterprise Big Data Framework written by Jan-Willem Middelburg and has been published by Kogan Page Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-03 with Business & Economics categories.
Businesses who can make sense of the huge influx and complexity of data will be the big winners in the information economy. This comprehensive guide covers all the aspects of transforming enterprise data into value, from the initial set-up of a big data strategy, towards algorithms, architecture and data governance processes. Using a vendor-independent approach, The Enterprise Big Data Framework offers practical advice on how to develop data-driven decision making, detailed data analysis and data engineering techniques. With a focus on practical implementation, The Enterprise Big Data Framework introduces six critical capabilities that every organization can use to become data driven. With sections on strategy formulation, data governance, sustainability, architecture and algorithms, this guide provides a comprehensive overview of best practices organizations can leverage to win in the data economy. Throughout the different sections, the book also introduces a capability model that every organization can use to measure progress. Endorsed by leading accreditation and examination institute AMPG International, this book is required reading for the Enterprise Big Data Certifications, which aim to develop excellence in big data practices across the globe. Online resources include sample data for practice purposes.
Multi Level Decision Making
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Author : Guangquan Zhang
language : en
Publisher: Springer
Release Date : 2015-02-07
Multi Level Decision Making written by Guangquan Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-07 with Technology & Engineering categories.
This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.