The potential and challenges of Big data - Recommendation systems next level application

TL;DR

This paper explores the vast potential of big data in enhancing recommendation systems, highlighting opportunities and challenges in analysis techniques and societal impact.

Contribution

It provides a comprehensive overview of big data analysis methods, opportunities, and challenges specifically related to improving recommendation systems.

Findings

Advanced analysis techniques enable better insights from big data.

Big data offers significant opportunities for recommendation systems.

Challenges include data management and privacy concerns.

Abstract

The continuous increase of data generated provides enormous possibilities of both public and private companies. The management of this mass of data or big data will play a crucial role in the society of the future, as it finds applications in different fields. There are so much potential and extremely useful insights hidden in the huge volume of data. The advanced analysis techniques available including predictive analytics, text mining, semantic analysis are needed to enable organizations to create a competitive advantage through data analyzed with different levels of sophistication, speed and accuracy previously unavailable. Therefore, is it still possible to have that level of sophistication with the ubiquitous numeric ocean that accompanies use every day via connected devices that invade our lives? However, development of big data requires a good understanding of the issues associated with it. And this is the purpose of this paper, which focuses on giving a close-up view of big data analysis, opportunities and challenges.