Article Title

An Architecture for Big Data Analytics

Authors

Joseph O. Chan, Roosevely University

Abstract

Big Data is the new experience curve in the new economy driven by data with high volume, velocity, variety, and veracity. They come from various sources that include the Internet, mobile devices, social media, geospatial devices, sensors, and other machine-generated data. Unlocking the value of Big Data allows business to better sense and respond to the environment, and is becoming a key to creating competitive advantages in a complex and rapidly changing market. Government is also taking notice of the Big Data phenomenon and has created initiatives to exploit Big Data in many areas such as science and engineering, healthcare and national security. Traditional data processing and analysis of structured data using RDBMS and data warehousing no longer satisfy the challenges of Big Data. Technology trends for Big Data embrace open source software, commodity servers, and massively parallel-distributed processing platforms. Analytics is at the core of exploiting values from Big Data to create consumable insights for business and government. This paper presents architecture for Big Data Analytics and explores Big Data technologies that include NoSQL databases, Hadoop Distributed File System and MapReduce.

Recommended Citation

Chan, Joseph O. (2013) "An Architecture for Big Data Analytics," Communications of the IIMA: Vol. 13: Iss. 2, Article 1.
DOI: https://doi.org/10.58729/1941-6687.1209
Available at: https://scholarworks.lib.csusb.edu/ciima/vol13/iss2/1