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Handbook Of Data Intensive Computing
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Book Synopsis Handbook of Data Intensive Computing by : Borko Furht
Download or read book Handbook of Data Intensive Computing written by Borko Furht and published by Springer Science & Business Media. This book was released on 2011-12-10 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Intensive Computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. The challenge of data intensive computing is to provide the hardware architectures and related software systems and techniques which are capable of transforming ultra-large data into valuable knowledge. Handbook of Data Intensive Computing is written by leading international experts in the field. Experts from academia, research laboratories and private industry address both theory and application. Data intensive computing demands a fundamentally different set of principles than mainstream computing. Data-intensive applications typically are well suited for large-scale parallelism over the data and also require an extremely high degree of fault-tolerance, reliability, and availability. Real-world examples are provided throughout the book. Handbook of Data Intensive Computing is designed as a reference for practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.
Book Synopsis Handbook of Data Intensive Computing by :
Download or read book Handbook of Data Intensive Computing written by and published by . This book was released on 2011-12-01 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Intensive Computing Applications for Big Data by : M. Mittal
Download or read book Data Intensive Computing Applications for Big Data written by M. Mittal and published by IOS Press. This book was released on 2018-01-31 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.
Book Synopsis Handbook of Data Intensive Computing by : Borko Furht
Download or read book Handbook of Data Intensive Computing written by Borko Furht and published by Springer Science & Business Media. This book was released on 2011-12-09 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Intensive Computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. The challenge of data intensive computing is to provide the hardware architectures and related software systems and techniques which are capable of transforming ultra-large data into valuable knowledge. Handbook of Data Intensive Computing is written by leading international experts in the field. Experts from academia, research laboratories and private industry address both theory and application. Data intensive computing demands a fundamentally different set of principles than mainstream computing. Data-intensive applications typically are well suited for large-scale parallelism over the data and also require an extremely high degree of fault-tolerance, reliability, and availability. Real-world examples are provided throughout the book. Handbook of Data Intensive Computing is designed as a reference for practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.
Book Synopsis Data-Intensive Computing by : Ian Gorton
Download or read book Data-Intensive Computing written by Ian Gorton and published by Cambridge University Press. This book was released on 2013 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes principles of the emerging field of data-intensive computing, along with methods for designing, managing and analyzing the big data sets of today.
Book Synopsis Handbook of Cloud Computing by : Borko Furht
Download or read book Handbook of Cloud Computing written by Borko Furht and published by Springer Science & Business Media. This book was released on 2010-09-11 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud computing has become a significant technology trend. Experts believe cloud computing is currently reshaping information technology and the IT marketplace. The advantages of using cloud computing include cost savings, speed to market, access to greater computing resources, high availability, and scalability. Handbook of Cloud Computing includes contributions from world experts in the field of cloud computing from academia, research laboratories and private industry. This book presents the systems, tools, and services of the leading providers of cloud computing; including Google, Yahoo, Amazon, IBM, and Microsoft. The basic concepts of cloud computing and cloud computing applications are also introduced. Current and future technologies applied in cloud computing are also discussed. Case studies, examples, and exercises are provided throughout. Handbook of Cloud Computing is intended for advanced-level students and researchers in computer science and electrical engineering as a reference book. This handbook is also beneficial to computer and system infrastructure designers, developers, business managers, entrepreneurs and investors within the cloud computing related industry.
Book Synopsis Cloud Computing by : Frederic Magoules
Download or read book Cloud Computing written by Frederic Magoules and published by CRC Press. This book was released on 2016-04-19 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis software. Addressing performance issues, Cloud Computing: Data-Intensive Computing and Scheduling explores the evolution of classical techniques and describes completely new methods and innovative algorithms. The
Book Synopsis Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management by : Kosar, Tevfik
Download or read book Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management written by Kosar, Tevfik and published by IGI Global. This book was released on 2012-01-31 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the challenges of distributed systems imposed by the data intensive applications, and on the different state-of-the-art solutions proposed to overcome these challenges"--Provided by publisher.
Book Synopsis Designing Data-Intensive Applications by : Martin Kleppmann
Download or read book Designing Data-Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Book Synopsis Data-Intensive Computing by : Ian Gorton
Download or read book Data-Intensive Computing written by Ian Gorton and published by . This book was released on 2012 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes principles of the emerging field of data-intensive computing, along with methods for designing, managing and analyzing the big data sets of today.
Book Synopsis Handbook of Research on Scalable Computing Technologies by : Li, Kuan-Ching
Download or read book Handbook of Research on Scalable Computing Technologies written by Li, Kuan-Ching and published by IGI Global. This book was released on 2009-07-31 with total page 1086 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents, discusses, shares ideas, results and experiences on the recent important advances and future challenges on enabling technologies for achieving higher performance"--Provided by publisher.
Book Synopsis Data Intensive Storage Services for Cloud Environments by : Kyriazis, Dimosthenis
Download or read book Data Intensive Storage Services for Cloud Environments written by Kyriazis, Dimosthenis and published by IGI Global. This book was released on 2013-04-30 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the evolution of digitized data, our society has become dependent on services to extract valuable information and enhance decision making by individuals, businesses, and government in all aspects of life. Therefore, emerging cloud-based infrastructures for storage have been widely thought of as the next generation solution for the reliance on data increases. Data Intensive Storage Services for Cloud Environments provides an overview of the current and potential approaches towards data storage services and its relationship to cloud environments. This reference source brings together research on storage technologies in cloud environments and various disciplines useful for both professionals and researchers.
Book Synopsis Designing Data-Intensive Applications by : Martin Kleppmann
Download or read book Designing Data-Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Book Synopsis Knowledge Management in the Development of Data-Intensive Systems by : Ivan Mistrik
Download or read book Knowledge Management in the Development of Data-Intensive Systems written by Ivan Mistrik and published by CRC Press. This book was released on 2021-06-15 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-intensive systems are software applications that process and generate Big Data. Data-intensive systems support the use of large amounts of data strategically and efficiently to provide intelligence. For example, examining industrial sensor data or business process data can enhance production, guide proactive improvements of development processes, or optimize supply chain systems. Designing data-intensive software systems is difficult because distribution of knowledge across stakeholders creates a symmetry of ignorance, because a shared vision of the future requires the development of new knowledge that extends and synthesizes existing knowledge. Knowledge Management in the Development of Data-Intensive Systems addresses new challenges arising from knowledge management in the development of data-intensive software systems. These challenges concern requirements, architectural design, detailed design, implementation and maintenance. The book covers the current state and future directions of knowledge management in development of data-intensive software systems. The book features both academic and industrial contributions which discuss the role software engineering can play for addressing challenges that confront developing, maintaining and evolving systems;data-intensive software systems of cloud and mobile services; and the scalability requirements they imply. The book features software engineering approaches that can efficiently deal with data-intensive systems as well as applications and use cases benefiting from data-intensive systems. Providing a comprehensive reference on the notion of data-intensive systems from a technical and non-technical perspective, the book focuses uniquely on software engineering and knowledge management in the design and maintenance of data-intensive systems. The book covers constructing, deploying, and maintaining high quality software products and software engineering in and for dynamic and flexible environments. This book provides a holistic guide for those who need to understand the impact of variability on all aspects of the software life cycle. It leverages practical experience and evidence to look ahead at the challenges faced by organizations in a fast-moving world with increasingly fast-changing customer requirements and expectations.
Book Synopsis Cloud Computing for Data-Intensive Applications by : Xiaolin Li
Download or read book Cloud Computing for Data-Intensive Applications written by Xiaolin Li and published by Springer. This book was released on 2014-12-02 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies. Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference.
Book Synopsis Foundations of Data Intensive Applications by : Supun Kamburugamuve
Download or read book Foundations of Data Intensive Applications written by Supun Kamburugamuve and published by John Wiley & Sons. This book was released on 2021-08-11 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: PEEK “UNDER THE HOOD” OF BIG DATA ANALYTICS The world of big data analytics grows ever more complex. And while many people can work superficially with specific frameworks, far fewer understand the fundamental principles of large-scale, distributed data processing systems and how they operate. In Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood, renowned big-data experts and computer scientists Drs. Supun Kamburugamuve and Saliya Ekanayake deliver a practical guide to applying the principles of big data to software development for optimal performance. The authors discuss foundational components of large-scale data systems and walk readers through the major software design decisions that define performance, application type, and usability. You???ll learn how to recognize problems in your applications resulting in performance and distributed operation issues, diagnose them, and effectively eliminate them by relying on the bedrock big data principles explained within. Moving beyond individual frameworks and APIs for data processing, this book unlocks the theoretical ideas that operate under the hood of every big data processing system. Ideal for data scientists, data architects, dev-ops engineers, and developers, Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood shows readers how to: Identify the foundations of large-scale, distributed data processing systems Make major software design decisions that optimize performance Diagnose performance problems and distributed operation issues Understand state-of-the-art research in big data Explain and use the major big data frameworks and understand what underpins them Use big data analytics in the real world to solve practical problems
Book Synopsis Data-Intensive Science by : Terence Critchlow
Download or read book Data-Intensive Science written by Terence Critchlow and published by CRC Press. This book was released on 2016-04-19 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-intensive science has the potential to transform scientific research and quickly translate scientific progress into complete solutions, policies, and economic success. But this collaborative science is still lacking the effective access and exchange of knowledge among scientists, researchers, and policy makers across a range of disciplines. Bringing together leaders from multiple scientific disciplines, Data-Intensive Science shows how a comprehensive integration of various techniques and technological advances can effectively harness the vast amount of data being generated and significantly accelerate scientific progress to address some of the world's most challenging problems. In the book, a diverse cross-section of application, computer, and data scientists explores the impact of data-intensive science on current research and describes emerging technologies that will enable future scientific breakthroughs. The book identifies best practices used to tackle challenges facing data-intensive science as well as gaps in these approaches. It also focuses on the integration of data-intensive science into standard research practice, explaining how components in the data-intensive science environment need to work together to provide the necessary infrastructure for community-scale scientific collaborations. Organizing the material based on a high-level, data-intensive science workflow, this book provides an understanding of the scientific problems that would benefit from collaborative research, the current capabilities of data-intensive science, and the solutions to enable the next round of scientific advancements.
