Modern Big Data Architectures

<p><b>Provides an up-to-date analysis of big data and multi-agent systems</b></p> <p>The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. <i>Modern Big Data Architectures </i>examines modern concepts and architecture for Big Data processing and analytics.</p> <p>This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book:</p> <ul> <li>Illustrates how data sets are produced and how they can be utilized in various areas of industry and science</li> <li>Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks</li> <li>Discusses current and emerging Big Data applications of Artificial Intelligence</li> </ul> <p><i>Modern Big Data Architectures: A Multi-Agent Systems Perspective </i>is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning. </p>