A Multi-Source Big Data Framework for Capturing and Analyzing Customer Feedback

Abstract

Big Data refers to the highly growing digital data collections that involve data with different formats, including structured, semi-structured, and unstructured datasets. Analyzing these combinations requires capabilities beyond the traditional database management systems' abilities. Among most sources of big data appears e-markets and social media platforms as significant contributors. This distinction is due to its features that facilitate consumers to express their views or opinions about specific products and services. Customer reviews and ratings become a significant resource for both consumers and firms regarding their plentiful and valuable knowledge. The proposed work introduces a big data framework to analyze such reviews and ratings, starting with data collection from different sources. Followed by integrating the collected data, which comes in different formats, toward the further processing phase. Finally, the analysis and visualization steps to draw the conclusions. Our work was tested on real data collected from active web resources.