Big Data Application Architecture Q&A : A Problem - Solution Approach / by Nitin Sawant, Himanshu Shah.

Format:

Book

Author/Creator:

Sawant, Nitin, Author.

Śāha, Himāṃśu, Author.

Series:

The Expert's Voice in Big Data

Language:

English

Subjects (All):

Big data.

Data structures (Computer science).

Big Data.

Data Structures and Information Theory.

Local Subjects:

Big Data.

Data Structures and Information Theory.

Physical Description:

1 online resource (XXI, 172 p. 92 illus.)

Edition:

1st ed. 2013.

Other Title:

Big data application architecture questions and answers

Place of Publication:

Berkeley, CA : Apress : Imprint: Apress, 2013.

Language Note:

English

System Details:

text file

Summary:

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.

Contents:

Big data introduction

Big data application architecture

Big data ingestion and streaming patterns

Big data storage patterns

Big data access patterns

Data discovery and analysis patterns

Big data visualization patterns

Big data deployment patterns

Big data NFRs

Big data case studies

Resources, references, and tools.

Notes:

Bibliographic Level Mode of Issuance: Monograph

Includes bibliographical references and index.

ISBN:

9781430262930

1430262931

OCLC:

870467654