Device Contextual Content Publishing in Media & Publishing Industry using Big Data Analytics on AWS
Girish G1, M. Prabhakar2
1Girish G, Department of C& IT, Reva University, Bangalore (Karnataka), India.
2Dr. Prabhakar M, Department of C&IT, Reva University, Bangalore (Karnataka), India.
Manuscript received on 05 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 29 June 2019 | PP: 250-254 | Volume-8 Issue-5S, May 2019 | Retrieval Number: E10500585S19/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Media & Publishing industry was traditionally a Paper and Print Industry. Since the revolution of Internet, industry started moving print to the digital form. Ever since the rapid penetration of mobile phones the media industry has rapidly scaled down paper publishing and adopted digital form successfully Internet speeds have also increased the adoption of Digital Print’s. With Newspapers being accessed globally in its digital form, it is extremely important for publishers to keep their content readily accessible and rich for various devices – Tablets, Laptops, Desktop’s, Mobile Phones, Smart Watches, Digital reader’s etc. This Paper talks about an ECONOMICAL & HIGHLY SCALABLE Big Data analytics implementation using AWS Elastic Map Reduce (EMR) to derive trends on end user usage patterns and choice of device. This will help the publishers rapidly scale to provide device contextual content to end users with ever changing access mechanisms.
Keywords: AWS-EMR, Big Data, Device-Contextual, Media & Publishing.
Scope of the Article: Big Data Analytics and Business Intelligence