Nostalgic Analysis of Big Data in Tourism by Business Intelligence

Surendra Kumar Reddy Koduru^1,

¹Business Intelligence and Reporting Lead, NC, USA

Cite this paper:
Surendra Kumar Reddy Koduru. Nostalgic Analysis of Big Data in Tourism by Business Intelligence. American Journal of Computing Research Repository. 2022; 7(1):1-6. doi: 10.12691/ajcrr-7-1-1

Abstract

There are several unsuccessful IT initiatives in today's market among specialized small and medium-sized businesses due to a lack of control over the gap between the business and its goal. In other words, purchased products are not being sold, which is a regular occurrence in tourism retail businesses. These firms buy several trip packages from large corporations, which then expire because of a lack of demand, resulting in a cost rather than an investment. To address this issue, we suggest detecting flaws that restrict a firm by re-engineering processes, creating a business architecture based on emotional analysis, and allowing small and medium-sized tourist companies (SMEs) to make better decisions and evaluate data. Most people have it but don't know how to use it. In addition, a case study was conducted using a real-world corporation, comparing data before and after utilizing the suggested model to confirm the model's practicality. Business knowledge has been a critical review topic in the travel industry for more than ten years. The growth of vast amounts of information has become more noticeable. Huge information summaries cover topics like combining large amounts of information from external sources (like web content), deleting data from an information source, particularly unstructured data (like customer reviews), and gradually absorbing information, depending on the context. Company knowledge and vast information are only beginning to reach their full potential for the traveler business. The aforementioned trends are becoming increasingly important for travel companies to stay up with, given the fundamental functionality and applicability of online entertainment and item reviews in the travel sector. More advanced IT, as well as new algorithms and methodologies, particularly in the areas of online content mining and text mining, open up new application domains for business intelligence approaches that have already attracted a lot of studies.

Keywords:
sentimental analysis tourism analysis big data analysis in tourism industry

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