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Client Data Caching : A Foundation Of High Performance Object Database Systems

RRP $629.99

Despite the significant ongoing work in the development of new database systems, many of the basic architectural and performance tradeoffs involved in their design have not previously been explored in a systematic manner. The designers of the various systems have adopted a wide range of strategies in areas such as process structure, client-server interaction, concurrency control, transaction management, and memory management. This monograph investigates several fundamental aspects of the emerging generation of database systems. It describes and investigates implementation techniques to provide high performance and scalability while maintaining the transaction semantics, reliability, and availability associated with more traditional database architectures. The common theme of the techniques developed here is the exploitation of client resources through caching-based data replication. Client Data Caching: A Foundation for High Performance Object Database Systems should be a value to anyone interested in the performance and architecture of distributed information systems in general and Object-based Database Management Systems in particular. It provides useful information for designers of such systems, as well as for practitioners who need to understand the inherent tradeoffs among the architectural alternatives in order to evaluate existing systems. Furthermore, many of the issues addressed in this book are relevant to other systems beyond the ODBMS domain. Such systems include shared-disk parallel database systems, distributed file systems, and distributed virtual memory systems. The presentation is suitable for practitioners and advanced students in all of these areas, although a basic understanding of database transaction semantics and techniques is assumed.


Family Office Database

RRP $13.99

The Family Office Database Guide provides you with 4.5 hours of webinar advice on raising capital from family offices along with two whitepapers on how the family office industry is evolving globally and how to create long-term partnerships in the industry. When you purchase this book you are receiving the transcript and video/audio access to four webinars that are normally sold for $99 each.This book is for those looking to work with HWN Investors, single family offices, multi-family offices, and those who want to leverage a family office directory or family office database product to help them do so.We run the #1 largest family office association, have a bestselling book in the industry, the #1 most visited website, and many conferences, and that is how we are able to offer this book, these webinars, and accurate family office data packages over the past 7+ years. Learn more about us at www.FamilyOfficeDatabases.com or by calling (212) 729-5067 to speak to our friendly team.


Mining Very Large Databases With Parallel Processing

RRP $931.99

Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms.
The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers.
It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science.
The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.



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