Abstract
Today, expansive ventures depend on database frameworks to oversee their information and data. These databases are valuable for conducting day-by-day trade exchanges but do not provide information that could be used for analysis to make a strategic decision. A data warehouse also known as an informational database act as a central repository that accumulates historical data from various sources and multiple systems across the company, the analysis of which fosters strategic decisions. Data mining techniques and algorithms in conjunction with business intelligence tools were utilized to analyze, predict, forecast and make logical sense of the integrated data. The applicability of data warehouse was across various functional areas and different types of business. For instance, some domains of use cases with the likes of Health, Retail, Finance, Service, Manufacturing and so forth. This paper examined various implementations of data warehouses in the aviation industry and proposes a data warehouse design. The plan was clarified with a meticulous case study on comprehending airline passenger booking at various stages of its lifecycle through a data warehouse design utilizing the four-step dimensional modelling methodology enabling smart revenue management for airlines. The primary beneficiaries of this article are academics, data warehouse and database administrators, data scientists (data mining and Business intelligence specialist), airline operators, management team, and functional silos across the business who would need passenger-booking intakes to make strategic decisions.
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Gounder, P., Kumar, K. (2023). Perceiving Airline Passenger Booking Lifecycle with the Utilization of Data Warehouse. In: Hsu, CH., Xu, M., Cao, H., Baghban, H., Shawkat Ali, A.B.M. (eds) Big Data Intelligence and Computing. DataCom 2022. Lecture Notes in Computer Science, vol 13864. Springer, Singapore. https://doi.org/10.1007/978-981-99-2233-8_18
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