Training Students to Extract Value from Big Data Book

Training Students to Extract Value from Big Data


  • Author : National Research Council
  • Publisher : National Academies Press
  • Release Date : 2015-01-16
  • Genre: Mathematics
  • Pages : 66
  • ISBN 10 : 9780309314404

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Training Students to Extract Value from Big Data Excerpt :

As the availability of high-throughput data-collection technologies, such as information-sensing mobile devices, remote sensing, internet log records, and wireless sensor networks has grown, science, engineering, and business have rapidly transitioned from striving to develop information from scant data to a situation in which the challenge is now that the amount of information exceeds a human's ability to examine, let alone absorb, it. Data sets are increasingly complex, and this potentially increases the problems associated with such concerns as missing information and other quality concerns, data heterogeneity, and differing data formats. The nation's ability to make use of data depends heavily on the availability of a workforce that is properly trained and ready to tackle high-need areas. Training students to be capable in exploiting big data requires experience with statistical analysis, machine learning, and computational infrastructure that permits the real problems associated with massive data to be revealed and, ultimately, addressed. Analysis of big data requires cross-disciplinary skills, including the ability to make modeling decisions while balancing trade-offs between optimization and approximation, all while being attentive to useful metrics and system robustness. To develop those skills in students, it is important to identify whom to teach, that is, the educational background, experience, and characteristics of a prospective data-science student; what to teach, that is, the technical and practical content that should be taught to the student; and how to teach, that is, the structure and organization of a data-science program. Training Students to Extract Value from Big Data summarizes a workshop convened in April 2014 by the National Research Council's Committee on Applied and Theoretical Statistics to explore how best to train students to use big data. The workshop explored the need for training and curricula and coursework that should be included.

Critical Thinking for Strategic Intelligence Book

Critical Thinking for Strategic Intelligence


  • Author : Katherine Hibbs Pherson
  • Publisher : CQ Press
  • Release Date : 2020-08-14
  • Genre: Political Science
  • Pages : 464
  • ISBN 10 : 9781544374277

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Critical Thinking for Strategic Intelligence Excerpt :

With Critical Thinking for Strategic Intelligence, Katherine Hibbs Pherson and Randolph H. Pherson have updated their highly regarded, easy-to-use handbook for developing core critical thinking skills and analytic techniques. This indispensable text is framed around 20 key questions that all analysts must ask themselves as they prepare to conduct research, generate hypotheses, evaluate sources of information, draft papers, and ultimately present analysis, including: How do I get started? Where is the information I need? What is my argument? How do I convey my message effectively? The Third Edition includes suggested best practices for dealing with digital disinformation, politicization, and AI. Drawing upon their years of teaching and analytic experience, Pherson and Pherson provide a useful introduction to skills that are essential within the intelligence community.

Refining the Concept of Scientific Inference When Working with Big Data Book

Refining the Concept of Scientific Inference When Working with Big Data


  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release Date : 2017-02-24
  • Genre: Mathematics
  • Pages : 114
  • ISBN 10 : 9780309454476

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Refining the Concept of Scientific Inference When Working with Big Data Excerpt :

The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.

Big Data and Health Analytics Book

Big Data and Health Analytics


  • Author : Katherine Marconi
  • Publisher : CRC Press
  • Release Date : 2014-12-20
  • Genre: Business & Economics
  • Pages : 382
  • ISBN 10 : 9781482229257

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Big Data and Health Analytics Excerpt :

Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery.Written for healt

Data Science for Undergraduates Book

Data Science for Undergraduates


  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release Date : 2018-11-11
  • Genre: Education
  • Pages : 138
  • ISBN 10 : 9780309475594

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Data Science for Undergraduates Excerpt :

Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

Harnessing the Power of Analytics Book

Harnessing the Power of Analytics


  • Author : Leila Halawi
  • Publisher : Springer Nature
  • Release Date : 2022
  • Genre: Electronic books
  • Pages : null
  • ISBN 10 : 9783030897123

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Harnessing the Power of Analytics Excerpt :

This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they can be applied and explained within improving decisions.

Oceanographic and Marine Cross Domain Data Management for Sustainable Development Book

Oceanographic and Marine Cross Domain Data Management for Sustainable Development


  • Author : Diviacco, Paolo
  • Publisher : IGI Global
  • Release Date : 2016-09-23
  • Genre: Science
  • Pages : 425
  • ISBN 10 : 9781522507017

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Oceanographic and Marine Cross Domain Data Management for Sustainable Development Excerpt :

As human activity makes a greater impact on the environment, sustainability becomes an increasingly imperative goal. With the assistance of current technological innovations, environmental systems can be better preserved. Oceanographic and Marine Cross-Domain Data Management for Sustainable Development is a pivotal resource for the latest research on the collection of environmental data for sustainability initiatives and the associate challenges with this data acquisition. Highlighting various technological, scientific, semantic, and semiotic perspectives, this book is ideally designed for researchers, technology developers, practitioners, students, and professionals in the field of environmental science and technology.

Sustainable Development  Concepts  Methodologies  Tools  and Applications Book

Sustainable Development Concepts Methodologies Tools and Applications


  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release Date : 2017-10-31
  • Genre: Science
  • Pages : 1725
  • ISBN 10 : 9781522538189

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Sustainable Development Concepts Methodologies Tools and Applications Excerpt :

To maintain a healthy ecosystem for contemporary society, and for future generations, policies must be implemented to protect the environment. This can be achieved by consistent evaluation of new initiatives and strategies. Sustainable Development: Concepts, Methodologies, Tools, and Applications is a comprehensive source of scholarly information on the latest research for sustainability concerns across a multidisciplinary perspective. Highlighting a broad range of innovative topics such as renewable energy, urban development, and green technologies, this multi-volume book is ideally designed for academics, researchers, professionals, students, and practitioners interested in the preservation of the environment.

Gulf War and Health Book

Gulf War and Health


  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release Date : 2018-12-20
  • Genre: Medical
  • Pages : 518
  • ISBN 10 : 9780309478267

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Gulf War and Health Excerpt :

For the United States, the 1991 Persian Gulf War was a brief and successful military operation with few injuries and deaths. However, soon after returning from duty, a large number of veterans began reporting health problems they believed were associated with their service in the Gulf. At the request of Congress, the National Academies of Sciences, Engineering, and Medicine has been conducting an ongoing review of the evidence to determine veterans' long-term health problems and potential causes. Some of the health effects identified by past reports include post-traumatic stress disorders, other mental health disorders, Gulf War illness, respiratory effects, and self-reported sexual dysfunction. Veterans' concerns regarding the impacts of deployment-related exposures on their health have grown to include potential adverse effects on the health of their children and grandchildren. These concerns now increasingly involve female veterans, as more women join the military and are deployed to war zones and areas that pose potential hazards. Gulf War and Health: Volume 11 evaluates the scientific and medical literature on reproductive and developmental effects and health outcomes associated with Gulf War and Post-9/11 exposures, and designates research areas requiring further scientific study on potential health effects in the descendants of veterans of any era.

Thriving on Our Changing Planet Book

Thriving on Our Changing Planet


  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release Date : 2019-01-20
  • Genre: Science
  • Pages : 716
  • ISBN 10 : 9780309467575

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Thriving on Our Changing Planet Excerpt :

We live on a dynamic Earth shaped by both natural processes and the impacts of humans on their environment. It is in our collective interest to observe and understand our planet, and to predict future behavior to the extent possible, in order to effectively manage resources, successfully respond to threats from natural and human-induced environmental change, and capitalize on the opportunities â€" social, economic, security, and more â€" that such knowledge can bring. By continuously monitoring and exploring Earth, developing a deep understanding of its evolving behavior, and characterizing the processes that shape and reshape the environment in which we live, we not only advance knowledge and basic discovery about our planet, but we further develop the foundation upon which benefits to society are built. Thriving on Our Changing Planet presents prioritized science, applications, and observations, along with related strategic and programmatic guidance, to support the U.S. civil space Earth observation program over the coming decade.

Demystifying Big Data and Machine Learning for Healthcare Book

Demystifying Big Data and Machine Learning for Healthcare


  • Author : Prashant Natarajan
  • Publisher : CRC Press
  • Release Date : 2017-02-15
  • Genre: Medical
  • Pages : 210
  • ISBN 10 : 9781315389318

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Demystifying Big Data and Machine Learning for Healthcare Excerpt :

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Handbook of Statistical Analysis and Data Mining Applications Book

Handbook of Statistical Analysis and Data Mining Applications


  • Author : Robert Nisbet
  • Publisher : Elsevier
  • Release Date : 2017-11-09
  • Genre: Mathematics
  • Pages : 822
  • ISBN 10 : 9780124166455

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Handbook of Statistical Analysis and Data Mining Applications Excerpt :

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Adaptive and Adaptable Learning Book

Adaptive and Adaptable Learning


  • Author : Katrien Verbert
  • Publisher : Springer
  • Release Date : 2016-09-06
  • Genre: Education
  • Pages : 686
  • ISBN 10 : 9783319451534

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Adaptive and Adaptable Learning Excerpt :

This book constitutes the proceedings of the 11th European Conference on Technology Enhanced Learning, EC-TEL 2016, held in Lyon, France, in September 2016. The 26 full papers, 23 short papers, 8 demo papers, and 33 poster papers presented in this volume were carefully reviewed and selected from 148 submissions.

Envisioning the Data Science Discipline Book

Envisioning the Data Science Discipline


  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release Date : 2018-03-05
  • Genre: Education
  • Pages : 68
  • ISBN 10 : 9780309465052

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Envisioning the Data Science Discipline Excerpt :

The need to manage, analyze, and extract knowledge from data is pervasive across industry, government, and academia. Scientists, engineers, and executives routinely encounter enormous volumes of data, and new techniques and tools are emerging to create knowledge out of these data, some of them capable of working with real-time streams of data. The nation's ability to make use of these data depends on the availability of an educated workforce with necessary expertise. With these new capabilities have come novel ethical challenges regarding the effectiveness and appropriateness of broad applications of data analyses. The field of data science has emerged to address the proliferation of data and the need to manage and understand it. Data science is a hybrid of multiple disciplines and skill sets, draws on diverse fields (including computer science, statistics, and mathematics), encompasses topics in ethics and privacy, and depends on specifics of the domains to which it is applied. Fueled by the explosion of data, jobs that involve data science have proliferated and an array of data science programs at the undergraduate and graduate levels have been established. Nevertheless, data science is still in its infancy, which suggests the importance of envisioning what the field might look like in the future and what key steps can be taken now to move data science education in that direction. This study will set forth a vision for the emerging discipline of data science at the undergraduate level. This interim report lays out some of the information and comments that the committee has gathered and heard during the first half of its study, offers perspectives on the current state of data science education, and poses some questions that may shape the way data science education evolves in the future. The study will conclude in early 2018 with a final report that lays out a vision for future data science education.

Advanced Deep Learning Applications in Big Data Analytics Book

Advanced Deep Learning Applications in Big Data Analytics


  • Author : Bouarara, Hadj Ahmed
  • Publisher : IGI Global
  • Release Date : 2020-10-16
  • Genre: Computers
  • Pages : 351
  • ISBN 10 : 9781799827931

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Advanced Deep Learning Applications in Big Data Analytics Excerpt :

Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.