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This edited book collects state-of-the-art research related to large-scale data analytics that has been accomplished over the last few;
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transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings;
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This book constitutes refereed proceedings of the 4th International Workshop on Software Foundations for Data Interoperability, SFDI 2020;
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data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for;
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Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the;
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This book presents applications of machine learning techniques in processing multimedia large-scale data. Multimedia such as text, image;
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Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and;
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Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques;
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Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques;
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The promises offered by Big Data¿driven decision making have been recognized broadly. Once the domain of only the heaviest of hitters;
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Plain English guidance for strategic business analytics and big data implementation In today's challenging economy, business analytics and;
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The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and;
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of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale;
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of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale;
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The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and;
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efficiently store, query, ingest, and learn from their data in a convenient framework. With this book, you'll examine how to analyze data at scale to;
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Modern applications in engineering and data science are increasingly based on multidimensional data of exceedingly high volume, variety;
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The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and;
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Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and;
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A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today's often;
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A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today's often;
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computing. The topics of interest included into this volume are: HP software tools, Parallel Algorithms and Scalability, HPC in Big Data analytics;
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Learn to extract actionable insights from your big data in real time using a range of Microsoft Azure features Key Features Updated;
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Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable;
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Data analysis models and techniques have rapidly evolved in last few decades to unfold patterns and information from large and complex;
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Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins;
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This book presents a language integrated query framework for big data. The continuous, rapid growth of data information to volumes of up to;
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