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Big Data Application Architecture Q&A - A Problem-Solution Approach torrent


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Torrent added:2014-01-01 00:00:00

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Big Data Application Architecture Q&A - A Problem-Solution Approach
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Nitin Sawant, Himanshu Shah, "Big Data Application Architecture Q&A: A Problem - Solution Approach"
English | ISBN: 1430262923 | 2013 | 172 pages | PDF | 7 MB

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 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.
Major considerations in building a big data solution
Big data application architectures problems for specific industries
What are the components one needs to build and end-to-end big data solution?
Does one really need a real-time big data solution or an off-line analytics batch solution?
What are the operations and support architectures for a big data solution?
What are the scalability considerations, and options for a Hadoop installation?

Who this book is for

CIOs, CTOs, enterprise architects, and software architects
Consultants, solution architects, and information management (IM) analysts who want to architect a big data solution for their enterprise

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