Abstract

Business Intelligence (BI) is a collection of tools, technologies, and practices that include the entire process of collecting, processing, and analyzing qualitative information, to help entrepreneurs better understand their business and marketplace. Every day, social networks expand at a faster rate and pace, which sees them as a source of Big Data. Therefore, BI is developed in the same way on VoC (Voice of Customer) expressed in social media as qualitative data for company decision-makers, who desire to have a clear perception of customers’ behaviour. In this article, we present a comparative study between traditional BI and social BI, then examine an approach to social business intelligence. Next, we are going to demonstrate the power of Big Data that can be integrated into BI so that we can finally describe in detail how Big Data technologies, like Apache Flume, help to collect unstructured data from various sources such as social media networks and store it in Hadoop storage.

Highlights

  • In recent years, the processing and analysis of large Business Intelligence (BI)-oriented data have advanced

  • Big Data will have a significant impact on Business Intelligence, especially for social business intelligence, which utilizes and analyzes enormous metadata generated in real-time by social networks

  • We discussed the importance of business intelligence regarding the vast data volume of social media to provide real-time analysis of the content shared on social media

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Summary

Introduction

The processing and analysis of large BI-oriented data have advanced. Social networks are an essential aspect of the information infrastructure These social media sites have attained an unparalleled degree of penetration for users, customers, and enterprises to provide the professional environment with a valuable information source, reduce costs, and offer quality support to multiple consumers. In this context, Big Data technologies are one of the most powerful and widely implemented technologies these days that meet the challenges of business intelligence. Understanding and interpreting the semantics of Big Data is today a challenge for companies that aim to understand customers' behaviour [2] better These analyses will lead and contribute to strategic decision-making

Traditional BI versus social BI
Conceptual Framework
Collect data
Classify data
Analyze Sentiments
Big Data integrated into Business intelligence
Channel
Conclusion and Future Work

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