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Big Data Analysis: Big Data Analysis Pipeline and Its Technical Challenges

Big Data Analysis: Big Data Analysis Pipeline and Its Technical Challenges
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Author(s): Rajanala Vijaya Prakash (S. R. Engineering College, India)
Copyright: 2016
Pages: 11
Source title: Effective Big Data Management and Opportunities for Implementation
Source Author(s)/Editor(s): Manoj Kumar Singh (Adama Science and Technology University, Ethiopia)and Dileep Kumar G. (Adama Science and Technology University, Ethiopia)
DOI: 10.4018/978-1-5225-0182-4.ch006

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Abstract

The data management industry has matured over the last three decades, primarily based on Relational Data Base Management Systems (RDBMS) technology. The amount of data collected and analyzed in enterprises has increased several folds in volume, variety and velocity of generation and consumption, organizations have started struggling with architectural limitations of traditional RDBMS architecture. As a result a new class of systems had to be designed and implemented, giving rise to the new phenomenon of “Big Data”. The data-driven world has the potential to improve the efficiencies of enterprises and improve the quality of our lives. There are a number of challenges that must be addressed to allow us to exploit the full potential of Big Data. This article highlights the key technical challenges of Big Data.

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