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Benefits Realization Management: Strategic Value from Portfolios, Programs, and Projects (Best Practices in Portfolio, Program, and Project Management)
by Carlos Eduardo SerraBenefits realization management (BRM) is a key part of governance, because it supports the strategic creation of value and provides the correct level of prioritization and executive support to the correct initiatives. Because of its relevance to the governance process, BRM has a strong influence over project success and is a link between strategic planning and strategy execution. This book guides portfolio, program, and project managers through the process of benefits realization management so they can maximize business value. It discusses why and how programs and projects are expected to enable value creation, and it explains the role of BRM in value creation. The book provides a flexible framework for: Translating business strategy drivers into expected benefits and explains the subsequent composition of a program and project portfolio that can realize expected benefits Planning the benefits realization expected from programs and projects and then making it happen Keeping programs and projects on track Reviewing and evaluating the benefits achieved or expected against the original baselines and the current expectations. To help project, program, and portfolio managers on their BRM journey, as well as to support business managers in executing business strategies, the book identifies key organizational responsibilities and roles involved in BRM practices, and it provides a simple reference that can be mapped against any organizational structure. A detailed and comprehensive case study illustrates each phase of the BRM framework as it links business strategy to project work, benefits, and business value. Each chapter ends with a series questions that provide a BRM self-assessment. The book concludes with a set of templates and detailed instructions to ensure successful deployment of BRM.
Beschaffung unter Berücksichtigung der IT-Sicherheit: Wichtigkeit, Herausforderungen und Maßnahmen (essentials)
by Ernst PillerErnst Piller gibt praktische Hinweise zum Beschaffungsvorgang von IT-sicherer Soft- und Hardware für die eigene Infrastruktur bzw. die Produktion. Dabei beschränkt sich ‚Hardware‘ nicht nur auf IKT-Produkte, sondern impliziert auch alle Geräte, Maschinen, Steuerungen, Fahrzeuge und Produktionskomponenten aus allen Branchen, die eine Software enthalten. Der Autor behandelt Themen wie IT-Sicherheitsanforderungen, Vertrauen in Hersteller, beschaffungsrelevante Informationssysteme für IT-Sicherheit und Gütezeichen. Abgerundet wird das essential mit der Vorstellung einer herstellerunabhängigen und kostenfreien Plattform zur Unterstützung des Beschaffungsprozesses für den Einkauf von Soft- und Hardware unter Berücksichtigung der IT-Sicherheit.
Best Practices for Teaching with Emerging Technologies (Best Practices in Online Teaching and Learning)
by Michelle Pacansky-BrockAs social media and Web 2.0 technologies continue to transform the learning trends and preferences of students, educators need to understand the applicability of these new tools in all types of learning environments. The second edition of Best Practices for Teaching with Emerging Technologies provides new and experienced instructors with practical examples of how low-cost and free technologies can be used to support student learning as well as best practices for integrating web-based tools into a course management system and managing student privacy in a Web 2.0 environment. "Showcase" spotlights throughout exemplify how the tools described in the book are already being used effectively in educational settings. This thoroughly revised second edition includes: a new chapter that explores how and why faculty are using the public web and open educational resources in place of a learning management system (LMS) and an expensive textbook additional tips and showcases in every chapter that illustrate faculty use of particular technologies the inclusion of new tools to replace technologies that no longer exist a revamped website featuring expanded online resources. This practical, easy-to-use guide will serve the needs of educators seeking to refresh or transform their instruction. Readers will be rewarded with an ample yet manageable collection of proven emerging technologies that can be leveraged for generating content, enhancing communications with and between students, and cultivating participatory, student-centered learning activities.
Best Practices in Engaging Online Learners Through Active and Experiential Learning Strategies (Best Practices in Online Teaching and Learning)
by Stephanie Smith Budhai Ke'Anna SkipwithBest Practices in Engaging Online Learners Through Active and Experiential Learning Strategies is a practical guide for all instructors and instructional designers working in online or blended learning environments who want to provide a supportive, engaging, and interactive learner experience. This book explores the integration of active and experiential learning approaches and activities including gamification, social media integration, and project- and scenario-based learning, as they relate to the development of authentic skill-building, communication, problem-solving, and critical-thinking skills in learners. Readers will find guidelines for the development of participatory peer-learning, cooperative education, and service learning opportunities in the online classroom. In addition, the authors provide effective learning strategies, resources, and tools that align learner engagement with course outcomes.
Betriebssysteme: Grundlagen und Konzepte
by Rüdiger BrauseDer Autor präsentiert die Grundlagen und Konzepte der heutigen Betriebssysteme und behandelt die Gebiete Prozesse (Prozesszustände, Prozessscheduling, Prozesssynchronisation und Prozesskommunikation), Speicherverwaltung (virtueller Speicher, paging, swapping), Dateiverwaltung (Files, Ordner, Sicherheitsmechanismen), Ein-und Ausgabeverwaltung (Treiber, I/O-memory mapping, Systemfunktionen) sowie Netzwerke (Netzwerkschichten, Arbeitsverteilung, Schattenserver) und Sicherheitsmechanismen (Angriffsarten, root kits, Kerberos). Dabei werden sowohl Einprozessor- als auch Mehrprozessorsysteme betrachtet und die Konzepte an wichtigen existierenden Betriebssystemen wie Unix und Windows NT verdeutlicht.In der vorliegenden vierten Auflage wurden viele Erfahrungen aus der Lehrpraxis berücksichtigt. So wurden nicht nur die Entwicklungen in Windows NT und Unix, speziell Linux, aktualisiert, sondern auch einige Kapitel neu gegliedert und um das Thema „Sicherheit“ ergänzt. Weitere Aufgaben und Beispiele mit Musterlösungen runden das Werk ab. Alle Vorlesungsfolien, die Vorlesungsvideos sowie eine umfangreiche Klausursammlung mit Musterlösungen stehen auf den Webseiten des Autors zum Herunterladen bereit.
Betriebssysteme kompakt (IT kompakt)
by Christian BaunSpeicherverwaltung, Hardwareverwaltung, Prozessadministration und Interprozesskommunikation sind zentrale Bereiche von Betriebssystemen. Die Konzepte und Prinzipien, auf denen klassische und moderne Betriebssysteme basieren, erl#65533;utert der Autor anhand von einschl#65533;gigen Aufgabenstellungen und L#65533;sungen. Das Werk gibt damit eine verst#65533;ndliche Einf#65533;hrung in die Architektur von Betriebssystemen und eignet sich deshalb auch f#65533;r die Lehre im Bachelorstudium.
Betriebswirtschaftliche Aspekte von Industrie 4.0 (ZfbF-Sonderheft #71/17)
by Mischa Seiter Lars Grünert Sebastian BerlinDas Sonderheft der ZfbF stellt die Ergebnisse des Arbeitskreises "Integrationsmanagement neuer Produkte" der Schmalenbach-Gesellschaft dar und zeigt facettenreich auf, wie umfassend die betriebswirtschaftliche Forschung bei der L#65533;sung der aufkommenden unternehmerischen Fragestellungen durch Industrie 4. 0 mitwirken kann. Industrie 4. 0 besch#65533;ftigt seit einigen Jahren die deutschen Unternehmen als eines von zehn Zukunftsprojekten der Bundesregierung. Die Untersuchung der betriebswirtschaftlichen Auswirkungen dieser Entwicklungen bildete, bis auf wenige Ausnahmen, einen Randaspekt der Forschung. Allerdings verursachten Industrie 4. 0-Initiativen in den letzten Jahren bereits weitreichende betriebswirtschaftliche Konsequenzen, die zum Teil ganze Branchen ver#65533;nderten. Wortmann, Bilgeri, Weinberger und Fleisch beleuchten die Entwicklung von Ertragsmodellen im Internet of Things. Die Autoren Gr#65533;nert und Sejdic leiten zun#65533;chst einen Bezugsrahmen f#65533;r Industrie 4. 0-getriebene Gesch#65533;ftsmodellinnovation ab. Kersten, Schr#65533;der und Indorf analysieren die Auswirkungen der Digitalisierung auf das Supply Chain Risikomanagement. Butschan, Nestle, Munck und Gleich befassen sich mit dem Kompetenzaufbau zur Umsetzung von Industrie 4. 0 in der Produktion. Schlie#65533;lich arbeiten Obermaier und Grottke die Herausforderungen von ,,Industrie 4. 0"-Technologien f#65533;r das Controlling heraus und zeigen das Potential dieser Technologien f#65533;r das Controlling auf.
Better PHP Development
by Bruno Skvorc Thomas Punt Younes Rafie Christopher Pitt Reza LavaryanPHP powers the vast majority of the web today. It is by far the most ubiquitous and accessible mature web language, and welcomes thousands of new developers every day. It is this ease of access that can, admittedly, sometimes give it a bad name - good resources are few and far in between, and the competition is real, driving people to take shortcuts, skip best practices, and learn on-the-fly. With PHP 7+ came some improvements that make it harder to make mistakes, and 7.2 is making things even safer, even more structured. If you're just getting started with the language (or perhaps youve been using it a while and have learned some bad habits), you're in luck. Not only will it be ever harder to slip up and make mistakes, but content such as this - hand picked from the excellent SitePoint PHP channel - will help you get started the right way. This collection comprises: How PHP Executes - from Source Code to Render by Thomas PuntGetting to Know and Love Xdebug by Bruno Ã…Â kvorcLocalization Demystified: Php-Intl for Everyone by Younes RafieEvent Sourcing in a Pinch by Christopher PittDisco with Design Patterns: A Fresh Look at Dependency Injection by Reza LavaryanA Comprehensive Guide to Using Cronjobs by Reza LavaryanEvent Loops in PHP by Christopher PittPDO - the Right Way to Access Databases in PHP by Parham DoustdarVagrant: The Right Way to Start with PHP by Bruno Ã…Â kvorc This book is suitable for beginner- to intermediate-level PHP developers.
Between the Public and Private in Mobile Communication (Routledge Studies in New Media and Cyberculture)
by Ana Serrano TelleríaMobile devices’ impact on daily life has raised relevant questions regarding public and private space and communication. Both the technological environment (operating systems, platforms, apps) and media ecosystems (interface design, participatory culture, social media) influence how users deal with the public and private, intimate and personal spheres. Leading researchers in communication, art, computer engineering, education, law, sociology, philosophy, and psychology here explore current methodologies for studying the dichotomy of the public and private in mobile communication, providing a foundation for further research.
Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation: 13th International Conference, BDAS 2017, Ustroń, Poland, May 30 - June 2, 2017, Proceedings (Communications in Computer and Information Science #716)
by Stanisław Kozielski, Dariusz Mrozek, Paweł Kasprowski, Bożena Małysiak-Mrozek and Daniel KostrzewaThis book constitutes the refereed proceedings of the 13th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2017, held in Ustroń, Poland, in May/June 2017.It consists of 44 carefully reviewed papers selected from 118 submissions. The papers are organized in topical sections, namely big data and cloud computing; artificial intelligence, data mining and knowledge discovery; architectures, structures and algorithms for efficient data processing; text mining, natural language processing, ontologies and semantic web; bioinformatics and biological data analysis; industrial applications; data mining tools, optimization and compression.
Beyond the Internet of Things: Everything Interconnected (Internet of Things)
by Constandinos X. Mavromoustakis George Mastorakis Jordi Mongay Batalla Evangelos PallisThe major subjects of the book cover modeling, analysis and efficient management of information in Internet of Everything (IoE) applications and architectures. As the first book of its kind, it addresses the major new technological developments in the field and will reflect current research trends, as well as industry needs. It comprises of a good balance between theoretical and practical issues, covering case studies, experience and evaluation reports and best practices in utilizing IoE applications. It also provides technical/scientific information about various aspects of IoE technologies, ranging from basic concepts to research grade material, including future directions.
BI and Big Data Management
by Philipp Strazny Ulrich HambuchCompanies increasingly recognize that the analysis of business information (business intelligence) can generate decisive competitive advantages. In addition, the compliance guidelines BCBS 239, Basel II and III, SOX, and Solvency II have led to legal requirements for a minimum level of quality in reporting and planning data and processes. The establishment of enterprise-wide data management thus continues to be one of the major challenges for IT and management in the years to come. Data quality is an integral success factor in the establishment of an optimal information infrastructure. A 2002 study from "The Data Warehousing Institutes" (TDWI) calculates that poor data quality in the US cost about $622 billion. Gartner market research stated in 2006: Poor data quality costs a typical organization 20% of revenue…. The worldwide financial and economic crisis after 2007 can retrospectively also be regarded as a data quality crisis. Despite far-reaching compliance requirements, many financial service companies have not been able to aggregate and prepare their risk data in a way to adequately control their risks, and they are still struggling in 2017. In the era of Big Data, data is viewed as the new oil and the available data volume worldwide multiplies every year. The requirements for transparency and data stream quality continue to increase, because these are considered essential for partially or completely new applications in decision support and other areas. But what use are larger data piles when quality and origin remain uncertain and when the costs for development and operation in data maintenance, integration, and analysis are proportional to the data volume? "Data quality is not everything, but without quality of data, it is all nothing." Metadata and metadata management are important aids for ensuring adequate data quality. The goal of this book is to take the current concepts and trends and tune th
The Big Book of Graphic Novels for Minecrafters: Three Unofficial Adventures
by Megan Miller Cara StevensPhoenix, a young miner girl, has never known her parents. She has always dreamed of something greater, of seeing the world outside her village and the magical forest that lies just beyond the walls. One day she takes the risk—just a quick hop over the walls—but her forbidden trip changes the course of her life. Thrust into a world of zombies, creepers, witches, and magical monks, Phoenix finds the adventure she craved, but will she find the bravery she needs to save not only her village but the entire Overworld? Containing The Quest for the Golden Apple, Revenge of the Zombie Monks, and The Ender Eye Prophecy, The Big Book of Graphic Novels for Minecrafters will enchant readers of all ages who love playing Minecraft and love stories full of action, adventure, and bravery. <P><P> <i>Advisory: Bookshare has learned that this book offers only partial accessibility. We have kept it in the collection because it is useful for some of our members. Benetech is actively working on projects to improve accessibility issues such as these.</i>
Big Data Analytics: Tools and Technology for Effective Planning (Chapman & Hall/CRC Big Data Series)
by Arun K. Somani Ganesh Chandra DekaThe proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.
Big Data Analytics: 5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings (Lecture Notes in Computer Science #10721)
by P. Krishna Reddy, Ashish Sureka, Sharma Chakravarthy and Subhash BhallaThis book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.
Big Data Analytics and Knowledge Discovery: 19th International Conference, DaWaK 2017, Lyon, France, August 28–31, 2017, Proceedings (Lecture Notes in Computer Science #10440)
by Ladjel Bellatreche and Sharma ChakravarthyThis book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017.The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in the following topical sections: new generation data warehouses design; cloud and NoSQL databases; advanced programming paradigms; non-functional requirements satisfaction; machine learning; social media and twitter analysis; sentiment analysis and user influence; knowledge discovery; and data flow management and optimization.
Big-Data Analytics for Cloud, IoT and Cognitive Learning
by Kai Hwang Min ChenThe definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.
Big Data Analytics Using Multiple Criteria Decision-Making Models (Operations Research Series)
by Ramakrishnan Ramanathan, Muthu Mathirajan, and A. Ravi RavindranMultiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data.
Big Data Analytics with Applications in Insider Threat Detection
by Bhavani Thuraisingham Pallabi Parveen Mohammad Mehedy Masud Latifur KhanToday's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.
Big Data Analytics with Java
by Rajat MehtaLearn the basics of analytics on big data using Java, machine learning and other big data tools About This Book • Acquire real-world set of tools for building enterprise level data science applications • Surpasses the barrier of other languages in data science and learn create useful object-oriented codes • Extensive use of Java compliant big data tools like apache spark, Hadoop, etc. Who This Book Is For This book is for Java developers who are looking to perform data analysis in production environment. Those who wish to implement data analysis in their Big data applications will find this book helpful. What You Will Learn • Start from simple analytic tasks on big data • Get into more complex tasks with predictive analytics on big data using machine learning • Learn real time analytic tasks • Understand the concepts with examples and case studies • Prepare and refine data for analysis • Create charts in order to understand the data • See various real-world datasets In Detail This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset. This book is an end-to-end guide to implement analytics on big data with Java. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analytics on big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naive Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networks on big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world. Style and approach The approach of book is to deliver practical learning modules in manageable content. Each chapter is a self-contained unit of a concept in big data analytics. Book will step by step builds the competency in the area of big data analytics. Examples using real world case studies to give ideas of real applications and how to use the techniques mentioned. The examples and case studies will be shown using both theory and code.
Big Data Analytics with SAS
by David PopeLeverage the capabilities of SAS to process and analyze Big Data About This Book • Combine SAS with platforms such as Hadoop, SAP HANA, and Cloud Foundry-based platforms for effecient Big Data analytics • Learn how to use the web browser-based SAS Studio and iPython Jupyter Notebook interfaces with SAS • Practical, real-world examples on predictive modeling, forecasting, optimizing and reporting your Big Data analysis with SAS Who This Book Is For SAS professionals and data analysts who wish to perform analytics on Big Data using SAS to gain actionable insights will find this book to be very useful. If you are a data science professional looking to perform large-scale analytics with SAS, this book will also help you. A basic understanding of SAS will be helpful, but is not mandatory. What You Will Learn • Configure a free version of SAS in order do hands-on exercises dealing with data management, analysis, and reporting. • Understand the basic concepts of the SAS language which consists of the data step (for data preparation) and procedures (or PROCs) for analysis. • Make use of the web browser based SAS Studio and iPython Jupyter Notebook interfaces for coding in the SAS, DS2, and FedSQL programming languages. • Understand how the DS2 programming language plays an important role in Big Data preparation and analysis using SAS • Integrate and work efficiently with Big Data platforms like Hadoop, SAP HANA, and cloud foundry based systems. In Detail SAS has been recognized by Money Magazine and Payscale as one of the top business skills to learn in order to advance one's career. Through innovative data management, analytics, and business intelligence software and services, SAS helps customers solve their business problems by allowing them to make better decisions faster. This book introduces the reader to the SAS and how they can use SAS to perform efficient analysis on any size data, including Big Data. The reader will learn how to prepare data for analysis, perform predictive, forecasting, and optimization analysis and then deploy or report on the results of these analyses. While performing the coding examples within this book the reader will learn how to use the web browser based SAS Studio and iPython Jupyter Notebook interfaces for working with SAS. Finally, the reader will learn how SAS's architecture is engineered and designed to scale up and/or out and be combined with the open source offerings such as Hadoop, Python, and R. By the end of this book, you will be able to clearly understand how you can efficiently analyze Big Data using SAS. Style and approach The book starts off by introducing the reader to SAS and the SAS programming language which provides data management, analytical, and reporting capabilities. Most chapters include hands on examples which highlights how SAS provides The Power to Know©. The reader will learn that if they are looking to perform large-scale data analysis that SAS provides an open platform engineered and designed to scale both up and out which allows the power of SAS to combine with open source offerings such as Hadoop, Python, and R.
Big Data and Cloud Computing for Development: Lessons from Key Industries and Economies in the Global South
by Diana Carolina Rojas Torres Nir Kshetri Torbjörn FredrikssonThis book provides a framework for evaluating big data and cloud computing based on how they evolve to fit users’ needs in developing countries in key areas, such as agriculture and education. The authors discuss how this framework can be utilized by businesses, governments, and consumers to accelerate economic growth and overcome information and communication barriers. By examining the ways in which cloud computing can drive social, economic, and environmental transformation, readers gain a nuanced understanding of the opportunities and challenges these technologies offer. The authors also provide an authoritative and up-to-date account of big data’s diffusion into a wide range of developing economies, such as Brazil and China, illustrating key concepts through in-depth case studies. Special attention is paid to economic development in the context of the new Sustainable Development Goals formulated by the United Nations, introducing readers to the most modern standard of economic evaluation. Students of information management, entrepreneurship, and development, as well as policy makers, researchers, and practitioners, will find Big Data and Cloud Computing for Development an interesting read and a useful reference source.
Big Data and Social Science: A Practical Guide to Methods and Tools
by Julia Lane Frauke Kreuter Ian Foster Rayid Ghani Ron S. JarminBig Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations.
Big Data and Visual Analytics
by Sang C. Suh Thomas AnthonyThis book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.
Big Data-Enabled Nursing: Education, Research and Practice (Health Informatics)
by Charlotte A. Weaver Connie W. Delaney Judith J. Warren Thomas R. Clancy Roy L. SimpsonHistorically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors.