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Author: Boris Delibašić
Publisher: Springer
ISBN: 3319185330
Category : Computers
Languages : en
Pages : 124
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Book Description
This book constitutes the refereed proceedings of the First International Conference on Decision Support Systems Technology, ICDSST 2015, held in Belgrade, Serbia, in May 2015. The theme of the event was “Big Data Analytics for Decision-Making” and it was organized by the EURO (Association of European Operational Research Societies) working group of Decision Support Systems (EWG-DSS). The eight papers presented in this book were selected out of 26 submissions after being carefully reviewed by at least three internationally known experts from the ICDSST 2015 Program Committee and external invited reviewers. The selected papers are representative of current and relevant research activities in the area of decision support systems, such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluations and analysis through social networks, and decision support system applications in real-world environments. The volume is completed by an additional invited paper on big data decision-making use cases.
Author: Boris Delibašić
Publisher: Springer
ISBN: 3319185330
Category : Computers
Languages : en
Pages : 124
Get Book Here
Book Description
This book constitutes the refereed proceedings of the First International Conference on Decision Support Systems Technology, ICDSST 2015, held in Belgrade, Serbia, in May 2015. The theme of the event was “Big Data Analytics for Decision-Making” and it was organized by the EURO (Association of European Operational Research Societies) working group of Decision Support Systems (EWG-DSS). The eight papers presented in this book were selected out of 26 submissions after being carefully reviewed by at least three internationally known experts from the ICDSST 2015 Program Committee and external invited reviewers. The selected papers are representative of current and relevant research activities in the area of decision support systems, such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluations and analysis through social networks, and decision support system applications in real-world environments. The volume is completed by an additional invited paper on big data decision-making use cases.
Author: Min Chen
Publisher: Springer
ISBN: 331906245X
Category : Computers
Languages : en
Pages : 100
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Book Description
This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis. For each phase, the book introduces the general background, discusses technical challenges and reviews the latest advances. Technologies under discussion include cloud computing, Internet of Things, data centers, Hadoop and more. The authors also explore several representative applications of big data such as enterprise management, online social networks, healthcare and medical applications, collective intelligence and smart grids. This book concludes with a thoughtful discussion of possible research directions and development trends in the field. Big Data: Related Technologies, Challenges and Future Prospects is a concise yet thorough examination of this exciting area. It is designed for researchers and professionals interested in big data or related research. Advanced-level students in computer science and electrical engineering will also find this book useful.
Author: Fausto Pedro García Márquez
Publisher: Springer
ISBN: 3319454986
Category : Computers
Languages : en
Pages : 274
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Book Description
This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.
Author: Mamta Mittal
Publisher: Springer
ISBN: 9811305501
Category : Computers
Languages : en
Pages : 275
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Book Description
The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.
Author: Ramesh Sharda
Publisher:
ISBN: 9781292341552
Category : Business intelligence
Languages : en
Pages : 832
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Book Description
For courses in decision support systems, computerized decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisionsAnalytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus -- analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT.
Author: Warkentin, Merrill
Publisher: IGI Global
ISBN: 1591400090
Category : Business & Economics
Languages : en
Pages : 307
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Book Description
In the mid 1990s, the widespread adoption of the web browser led to a rapid commercialization of the Internet. In addition, initial success stories were reported from companies that learned how to create an effective direct marketing channel ? selling tangible products to consumers directly with the World Wide Web. By the end of the 1990s, the next revolution began ? called business-to-business electronic commerce. Business to Business Electronic Commerce will provide researchers and practitioners alike with a source of knowledge related to this emerging area of business. The audience for this book includes students, scholars, researchers and practitioners. Any currently engaged in the utilization and management of electronic commerce technologies will be interested in Business to Business Electronic Commerce to learn about the latest issues and challenges facing businesses throughout the world.
Author: Boris Delibašić
Publisher:
ISBN: 9783319185347
Category :
Languages : en
Pages :
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Book Description
This book constitutes the refereed proceedings of the First International Conference on Decision Support Systems Technology, ICDSST 2015, held in Belgrade, Serbia, in May 2015. The theme of the event was "Big Data Analytics for Decision-Making" and it was organized by the EURO (Association of European Operational Research Societies) working group of Decision Support Systems (EWG-DSS). The eight papers presented in this book were selected out of 26 submissions after being carefully reviewed by at least three internationally known experts from the ICDSST 2015 Program Committee and external invited reviewers. The selected papers are representative of current and relevant research activities in the area of decision support systems, such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluations and analysis through social networks, and decision support system applications in real-world environments. The volume is completed by an additional invited paper on big data decision-making use cases.
Author: Karen L. Webber
Publisher: Johns Hopkins University Press
ISBN: 1421439034
Category : Education
Languages : en
Pages : 337
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Book Description
How data-informed decision making can make colleges and universities more effective institutions. The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities. Aimed at senior administrative leaders, practitioners of institutional research, technology professionals, and graduate students in higher education, the book opens with a conceptual discussion of the roles that data analytics can play in higher education administration. Subsequent chapters address recent developments in technology, the rapid accumulation of data assets, organizational maturity in building analytical capabilities, and methodological advancements in developing predictive and prescriptive analytics. Each chapter includes a literature review of the research and application of analytics developments in their respective functional areas, a discussion of industry trends, examples of the application of data analytics in their decision process, and other related issues that readers may wish to consider in their own organizational environment to find opportunities for building robust data analytics capabilities. Using a series of focused discussions and case studies, Big Data on Campus helps readers understand how analytics can support major organizational functions in higher education, including admission decisions, retention and enrollment management, student life and engagement, academic and career advising, student learning and assessment, and academic program planning. The final section of the book addresses major issues and human factors involved in using analytics to support decision making; the ethical, cultural, and managerial implications of its use; the role of university leaders in promoting analytics in decision making; and the need for a strong campus community to embrace the analytics revolution. Contributors: Rana Glasgal, J. Michael Gower, Tom Gutman, Brian P. Hinote, Braden J. Hosch, Aditya Johri, Christine M. Keller, Carrie Klein, Jaime Lester, Carrie Hancock Marcinkevage, Gail B. Marsh, Susan M. Menditto, Jillian N. Morn, Valentina Nestor, Cathy O'Bryan, Huzefa Rangwala, Timothy Renick, Charles Tegen, Rachit Thariani, Chris Tompkins, Lindsay K. Wayt, Karen L. Webber, Henry Y. Zheng, Ying Zhou
Author: Paulo Sérgio Abreu Freitas
Publisher: EWG-DSS
ISBN: 9898805447
Category : Business & Economics
Languages : en
Pages : 265
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Book Description
Author: Jorge Marx Gómez
Publisher: Springer Nature
ISBN: 3031154207
Category : Business & Economics
Languages : en
Pages : 599
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Book Description
This book presents case studies to analyse the relationship between sustainability – environmental, social, institutional and economic – and digital innovation. The respective contributions offer a contextualisation of the main present and future trends concerning these two elements, and present analyses from economic, technical, managerial, and social perspectives alike. The individual sections of the book focus on interactions between sustainability and digital innovation in existing organisations and highlight the new opportunities, challenges and threats that may emerge as a result. The contributions are mainly based on case studies and research conducted in Europe and Africa, with a few focusing on Southeast Asia and Central America, and were prepared by experts in the fields of Information Systems, Computer Science, Social Development, and Economics.
