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Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Discover how Apache Hadoop can unleash the power of your data. This comprehensive resource shows you how to build and maintain reliable, scalable, distributed systems with the Hadoop framework -- an open source implementation of MapReduce, the algorithm on which Google built its empire. Programmers will find details for analyzing datasets of any size, and administrators will learn how to set up and run Hadoop clusters. This revised edition covers recent changes to Hadoop, including new features such as Hive, Sqoop, and Avro. It also provides illuminating case studies that illustrate how Hadoop is used to solve specific problems. Looking to get the most out of your data? This is your book. Use the Hadoop Distributed File System (HDFS) for storing large datasets, then run distributed computations over those datasets with MapReduce Become familiar with Hadoop’s data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase, Hadoop’s database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems "Now you have the opportunity to learn about Hadoop from a master -- not only of the technology, but also of common sense and plain talk." --Doug Cutting, Cloudera
Providing a reliable supply of water requires being prepared for water shortages of varying degree and duration. What can a municipal water supplier do to mitigate water shortages caused by drought? Preparing for drought and water shortages before they occur is the best defense. This manual will help water managers facing water shortages by illustrating how to employ tried-and-true strategies and tactics of drought mitigation, as well as new tools and methods. Managing water shortages involves temporarily reducing demand and finding alternate water to temporarily increase supply. There are options available to water managers to accomplish this. The manual provides a proven, seven-step process to anticipate and respond to water shortages through a structured planning process.
Comprehensive and fully up to date, Dr. Peter Neligan's six-volume masterwork, Plastic Surgery, 5th Edition, remains the gold standard text in this complex area of surgery. Completely revised to meet the demands of both the trainee and experienced surgeon, it features new, full-color clinical photos, procedural videos, and lectures across all six volumes. Bonus material online includes additional text, images, and over 200 procedural videos that help you improve your mastery of the latest techniques. - Easily find the answers you need with an organization that features separate volumes covering Principles • Aesthetic • Craniofacial, Head and Neck Surgery and Pediatric Plastic Surgery • Lower Extremity, Trunk and Burns • Breast • and Hand and Upper Extremity. Each easily readable, individual volume is a standalone comprehensive text full of salient and applicable anatomy and techniques. - Key procedures include gender affirmation management and surgery, microsurgery and surgery for lymphedema, aesthetic facial surgery, aesthetic body surgery, and the education, training and practice of plastic surgery. - New digital video preface by Dr. Neligan addresses the changes across all six volumes. - New treatment and decision-making algorithms added to chapters where applicable. - New video lectures and editor-narrated slide presentations offer a step-by-step audiovisual walkthrough of techniques and procedures. - Four new international experts join the editorial team, and lead editor Peter C. Neligan creates a cohesive tone throughout the chapters and content across all six volumes. - Evidence-based advice from a diverse collection of experts allows you to apply the very latest advances in every area of plastic surgery and ensure optimal outcomes. - Purchase only the volumes you need or own the entire set, with the ability to search across all six volumes online!
"This comprehensive, six-volume collection addresses all aspects of online and distance learning, including information communication technologies applied to education, virtual classrooms, pedagogical systems, Web-based learning, library information systems, virtual universities, and more. It enables libraries to provide a foundational reference to meet the information needs of researchers, educators, practitioners, administrators, and other stakeholders in online and distance learning"--Provided by publisher.
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA "Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us." -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
e-Learning Ecologies explores transformations in the patterns of pedagogy that accompany e-learning—the use of computing devices that mediate or supplement the relationships between learners and teachers—to present and assess learnable content, to provide spaces where students do their work, and to mediate peer-to-peer interactions. Written by the members of the "new learning" research group, this textbook suggests that e-learning ecologies may play a key part in shifting the systems of modern education, even as technology itself is pedagogically neutral. The chapters in this book aim to create an analytical framework with which to differentiate those aspects of educational technology that reproduce old pedagogical relations from those that are genuinely innovative and generative of new kinds of learning. Featuring case studies from elementary schools, colleges, and universities on the practicalities of new learning environments, e-Learning Ecologies elucidates the role of new technologies of knowledge representation and communication in bringing about change to educational institutions.
Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!