Big Data Storage Methods
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Handbook of Research on Big Data Storage and Visualization Techniques
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
Big Data Concepts, Technologies, and Applications
With the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data. These huge volumes of data can be used for effective decision making and improved performance if analyzed properly. Due to its inherent characteristics, big data is very complex and cannot be handled and processed by traditional database management approaches. There is a need for sophisticated approaches, tools and technologies that can be used to store, manage and analyze these enormous amounts of data to make the best use of them. Big Data Concepts, Technologies, and Applications covers the concepts, technologies, and applications of big data analytics. Presenting the state-of-the-art technologies in use for big data analytics. it provides an in-depth discussion about the important sectors where big data analytics has proven to be very effective in improving performance and helping industries to remain competitive. This book provides insight into the novel areas of big data analytics and the research directions for the scholars working in the domain. Highlights include: The advantages, disadvantages and challenges of big data analytics State-of-the-art technologies for big data analytics such as Hadoop, NoSQL databases, data lakes, deep learning and blockchain The application of big data analytic in healthcare, business, social media analytics, fraud detection and prevention and governance Exploring the concepts and technologies behind big data analytics, the book is an ideal resource for researchers, students, data scientists, data analysts and business analysts who need insight into big data analytics
Big Data
The illustrations in this book are created by “Team Educohack”. Big Data: Revolutionizing the Future delves into how big data has become a dominant paradigm, transforming various sectors and reshaping society. This book, divided into 13 chapters, provides a thorough examination of big data, discussing its applications, growth, and potential. We explore how big data approaches can revolutionize both business and health sectors, while also addressing the risks associated with datafication. Chapters 11 to 13 focus on the growth of big data in different sectors, detailing the expanding market and advancements in big data analytics. Chapters 5 to 10 offer insightful examples of big data's transformative potential. This book emphasizes the importance of grounding these perspectives in existing scientific methods to enhance their practical applicability. We also discuss the comprehensive understanding that comes from analyzing all available data, illustrating this with empirical examples. Big Data: Revolutionizing the Future presents a clear, accessible narrative, enriched with a wide range of examples, to help readers grasp the full implications and opportunities of big data.