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Author: Stephen Few Publisher: ISBN: 9781938377105 Category : Computers Languages : en Pages : 0
Book Description
Argues against the value of big data, suggesting that it is a marketing campaign that distracts from the real and important work of deriving value from data.
Author: Stephen Few Publisher: ISBN: 9781938377105 Category : Computers Languages : en Pages : 0
Book Description
Argues against the value of big data, suggesting that it is a marketing campaign that distracts from the real and important work of deriving value from data.
Author: Huddleston, R. J. Publisher: Edward Elgar Publishing ISBN: 1839101016 Category : Political Science Languages : en Pages : 801
Book Description
Drawing together international experts on research methods in International Relations (IR), this Handbook answers the complex practical questions for those approaching a new research topic for the first time. Innovative in its approach, it considers the art of IR research as well as the science, offering diverse perspectives on current research methods and emerging developments in the field.
Author: Tobias Macey Publisher: "O'Reilly Media, Inc." ISBN: 1492062383 Category : Computers Languages : en Pages : 263
Book Description
Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail
Author: Qian, Yufeng Publisher: IGI Global ISBN: 152257770X Category : Education Languages : en Pages : 351
Book Description
Higher education today faces several challenges including soaring cost, rising student debt, declining state support, and a staggering dropout rate. Digital technology enables numerous paths to innovation and promising solutions to these crises in higher education. However, few efforts have been made to look into the dynamic relationship between technology, innovation, and leadership and how they work together to transform teaching and learning, campus life, student service and support, administration, and university advancement. Technology Leadership for Innovation in Higher Education is a pivotal reference source that provides vital research on the intersection of technology, innovation, and leadership in higher education by examining the role of technology in activating, promoting, and accelerating innovation and by identifying challenges regarding technology leadership. While highlighting topics such as blended teaching, faculty development, and university advancement, this publication is ideally designed for teachers, principals, educational and IT management and staff, researchers, students, and stakeholders in higher education seeking current research on critical leadership dimensions required for effective education leaders.
Author: Nuno Martins Publisher: Springer Nature ISBN: 3030616711 Category : Architecture Languages : en Pages : 624
Book Description
This book reports on research findings and practical lessons featuring advances in: digital and interaction design; graphic design and branding; design strategies and methodologies; design education; society and communication in design practice; and other related areas. Gathering the proceedings of the 4th International Conference on Digital Design and Communication, Digicom 2020, held virtually on November 5-6, 2020, the book describes cutting-edge perspectives on and analysis of and solutions to challenges digital communication is currently presenting to society, institutions and brands. It offers a timely guide and a source of inspiration for designers of all kinds, including graphic, digital and web designers, UI, UX and social media designers, and to researchers, advertisers, artists, and entrepreneurs, as well as brand or corporate communication managers.
Author: Julia Schmitt Publisher: Cuvillier Verlag ISBN: 3736966016 Category : Business & Economics Languages : en Pages : 190
Book Description
Policymakers worldwide draft privacy laws to increase user privacy by imposing strict legal requirements. At the same time, policymakers grant websites a degree of freedom in implementing these requirements. However, the effects of privacy laws and the granted implementation freedom on websites and users remain unclear. Yet, when drafting privacy laws, policymakers need to trade-off between increasing user privacy and limiting the harm to websites’ ability to earn revenue with the collected user data. Similarly, websites need to anticipate such effects, e.g., on their revenues, when deciding how to implement privacy laws. This dissertation encompasses three articles to shed light on the effects of privacy laws and their granted implementation freedom on websites’ revenues and user privacy, using the enforcement of the EU’s General Data Protection Regulation (GDPR). The articles show that while the GDPR has average negative effects on websites’ revenues, these effects vary across websites’ chosen implementation of GPDR. The dissertation further shows that the different implementations of the legal requirements impact user privacy. Thereby, this dissertation provides an empirical foundation of privacy laws’ effects on websites’ revenues and user privacy, aiding policymakers in evaluating or drafting privacy laws and websites in deciding how to implement them.
Author: Kevin Garstki Publisher: Cotsen Institute of Archaeology Press ISBN: 1950446263 Category : Social Science Languages : en Pages : 226
Book Description
Every part of archaeological practice is intimately tied to digital technologies, but how deeply do we really understand the ways these technologies impact the theoretical trends in archaeology, how these trends affect the adoption of these technologies, or how the use of technology alters our interactions with the human past? This volume suggests a critical approach to archaeology in a digital world, a purposeful and systematic application of digital tools in archaeology. This is a call to pay attention to your digital tools, to be explicit about how you are using them, and to understand how they work and impact your own practice. The chapters in this volume demonstrate how this critical, reflexive approach to archaeology in the digital age can be accomplished, touching on topics that include 3D data, predictive and procedural modelling, digital publishing, digital archiving, public and community engagement, ethics, and global sustainability. The scale and scope of this research demonstrates how necessary it is for all archaeological practitioners to approach this digital age with a critical perspective and to be purposeful in our use of digital technologies.
Author: Raul Estrada Publisher: Apress ISBN: 1484221753 Category : Computers Languages : en Pages : 277
Book Description
Learn how to integrate full-stack open source big data architecture and to choose the correct technology—Scala/Spark, Mesos, Akka, Cassandra, and Kafka—in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer: The language: Scala The engine: Spark (SQL, MLib, Streaming, GraphX) The container: Mesos, Docker The view: Akka The storage: Cassandra The message broker: Kafka What You Will Learn: Make big data architecture without using complex Greek letter architectures Build a cheap but effective cluster infrastructure Make queries, reports, and graphs that business demands Manage and exploit unstructured and No-SQL data sources Use tools to monitor the performance of your architecture Integrate all technologies and decide which ones replace and which ones reinforce Who This Book Is For: Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer
Author: Martha L. Sylvia, PhD, MBA, RN Publisher: Springer Publishing Company ISBN: 0826163246 Category : Medical Languages : en Pages : 495
Book Description
Praise for the first edition: "DNP students may struggle with data management, since their projects are not research but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars -- Doody's Medical Reviews This unique text and reference—the only book to address the full spectrum of clinical data management for the DNP student—instills a fundamental understanding of how clinical data is gathered, used, and analyzed, and how to incorporate this data into a quality DNP project. The new third edition is updated to reflect changes in national health policy such as quality measurements, bundled payments for specialty care, and Advances to the Affordable Care Act (ACA) and evolving programs through the Centers for Medicare and Medicaid Services (CMS). The third edition reflects the revision of 2021 AACN Essentials and provides data sets and other examples in Excel and SPSS format, along with several new chapters. This resource takes the DNP student step-by-step through the complete process of data management, from planning through presentation, clinical applications of data management that are discipline-specific, and customization of statistical techniques to address clinical data management goals. Chapters are brimming with descriptions, resources, and exemplars that are helpful to both faculty and students. Topics spotlight requisite competencies for DNP clinicians and leaders such as phases of clinical data management, statistics and analytics, assessment of clinical and economic outcomes, value-based care, quality improvement, benchmarking, and data visualization. A progressive case study highlights multiple techniques and methods throughout the text. New to the Third Edition: New Chapter: Using EMR Data for the DNP Project New chapter solidifies link between EBP and Analytics for the DNP project New chapter highlights use of workflow mapping to transition between current and future state, while simultaneously visualizing process measures needed to ensure success of the DNP project Includes more examples to provide practical application exercises for students Key Features: Disseminates robust strategies for using available data from everyday practice to support trustworthy evaluation of outcomes Uses multiple tools to meet data management objectives [SPSS, Excel®, Tableau] Presents case studies to illustrate multiple techniques and methods throughout chapters Includes specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students Offers real world examples of completed DNP projects Provides Instructor’s Manual, PowerPoint slides, data sets in SPSS and Excel, and forms for completion of data management and evaluation plan
Author: Stephen Few
Author: Stephen Few
Author: Huddleston, R. J.
Author: Tobias Macey
Author: Qian, Yufeng
Author: Nuno Martins
Author: Julia Schmitt
Author: Kevin Garstki
Author: Raul Estrada
Author: Martha L. Sylvia, PhD, MBA, RN
Author: Viktor Mayer-Schönberger