big data application architecture (24 Ergebnisse)

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Taschenbuch. Zustand: Neu. Neuware -Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits.Big Data Application Architecture Pattern Recipes answers one of the most critical questions of this time 'how do you select the best end-to-end architecture to solve your big data problem '.The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution, trying to extract insight from huge volumes of data in real-time and across multiple relational and non-relational data types for clients from industries like retail, telecommunication, banking, and insurance. The patterns in this book provide the strong architectural foundation required to launch your next big data application.The architectures for realizing these opportunities are based on relatively less expensive and heterogeneous infrastructures compared to the traditional monolithic and hugely expensive options that exist currently. This book describes and evaluates the benefits of heterogeneity which brings with it multiple options of solving the same problem, evaluation of trade-offs and validation of 'fitness-for-purpose' of the solution.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 172 pp. Englisch.

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paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2023-04 Pages: 444 Publisher: Publishing House of Electronic Industry This book introduces how to use Python to implement enterprise-level big data full-stack development. design and programming. The knowledge points involved include overall data architecture design. data source and data collection. data synchronization. message queues. relational databases. NoSQL databases. batch processing. stream processing. graph computing. artificial intelligence. an.

paperback. Zustand: New. Wisdom Government of the road: big data. cloud computing. networking-based applications. Tsinghua University Press: Paperback. Pub Date :2014-05-01 Pages: 476 Language: Chinese Publisher is divided into seven parts. The first part is theoretical papers. focusing on the wisdom of the government role in the development process of virtual government. the important role of co-evolution methodology in the wisdom of the government building. The second part is the technical papers describing cloud c.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2016-12-01 Pages: 329 Publisher: tsinghua university press big data cloud services technical architecture and practice (big data technology and application for teaching) from the perspective of big data and cloud computing. big data systematically cloud architecture technology and practice of professional books. the book is divided into five chapter 19. respectively introduce large data of cloud computing is.

Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Use cases for big data specific to architectures like Walmart and Ebay. Covers the end-to-end application architecture required to realize the big data solution covering the analytics and visualization aspects in addition to hadoop and no.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits.Big Data Application Architecture Pattern Recipes answers one of the most critical questions of this time 'how do you select the best end-to-end architecture to solve your big data problem '.The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution, trying to extract insight from huge volumes of data in realtime and across multiple relational and non-relational data types for clients from industries like retail, telecommunication, banking, and insurance. The patterns in this book provide the strong architectural foundation required to launch your next big data application.The architectures for realizing these opportunities are based on relatively less expensive and heterogeneous infrastructures compared to the traditional monolithic and hugely expensive options that exist currently. This book describes and evaluates the benefits of heterogeneity which brings with it multiple options of solving the same problem, evaluation of trade-offs and validation of 'fitness-for-purpose' of the solution. 172 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits.Big Data Application Architecture Pattern Recipes answers one of the most critical questions of this time 'how do you select the best end-to-end architecture to solve your big data problem '.The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution, trying to extract insight from huge volumes of data in realtime and across multiple relational and non-relational data types for clients from industries like retail, telecommunication, banking, and insurance. The patterns in this book provide the strong architectural foundation required to launch your next big data application.The architectures for realizing these opportunities are based on relatively less expensive and heterogeneous infrastructures compared to the traditional monolithic and hugely expensive options that exist currently. This book describes and evaluates the benefits of heterogeneity which brings with it multiple options of solving the same problem, evaluation of trade-offs and validation of 'fitness-for-purpose' of the solution.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the medical field, data is increasingly growing and traditional methods cannot manage them efficiently. In the computational biomedical, the continuous challenges are management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of the data using machine learning and artificial intelligence techniques. It becomes very important to develop methods and/or architectures based on big data technologies for complete processing of biomedical images data. In this thesis, we propose a complete and optimal workflow based on big data technology and optimal algorithms drawn from literature to manage biomedical images. Compression step within the proposed optimal workflow will be considered as a study case implementing big data analysis technology. The proposed workflow implements an image compression algorithm for biomedical images, which is based on three main steps, orthogonal transform, vector quantization using machine learning and entropy encoding. The proposed algorithm allows us to develop appropriate and efficient methods to leverage a large number of images into the proposed workflow.

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