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Utilizing an Airline Data Warehouse for Website Data Analytics: A Conceptual Design

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Big Data Intelligence and Computing (DataCom 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13864))

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Abstract

As a result of the Covid-19 outbreak, airlines are focusing more on online booking engines, which require airlines to segment clients, target personalized offers, and monitor channel performance, advertising spend, goal conversion, and campaign effectiveness using web analytics data. To accommodate all of these aspects, as well as quick responses to current and future demands, enhanced planning, and alignment with corporate decision-making, a data warehouse is required. This study will illustrate how to integrate website data into a data warehouse as well as its data model using the snowflake schema. A thorough case study on understanding airline digital booking engine data at different stages of its lifecycle through a data warehouse architecture using the four-step dimensional modelling approach, allowing smart revenue management for airlines, provided more clarification of the strategy. This post will mostly benefit the airline’s digital team, data warehouse and database administrators, digital analysts, revenue management team, and functional segments throughout the organization that use digital passenger-booking inputs to make strategic choices.

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Authors and Affiliations

  1. Department of Computer Science and Mathematics, The University of Fiji, Lautoka, Fiji

    Ravnesh Kumar & Kunal Kumar

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  1. Ravnesh Kumar
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  2. Kunal Kumar
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Corresponding author

Correspondence to Kunal Kumar .

Editor information

Editors and Affiliations

  1. Asia University, Taichung, Taiwan

    Ching-Hsien Hsu

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Mengwei Xu

  3. University of New Brunswick, Fredericton, NB, Canada

    Hung Cao

  4. Asia University, Taichung, Taiwan

    Hojjat Baghban

  5. University of Fiji, Samabula, Fiji

    A. B. M. Shawkat Ali

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Kumar, R., Kumar, K. (2023). Utilizing an Airline Data Warehouse for Website Data Analytics: A Conceptual Design. 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_19

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  • DOI: https://doi.org/10.1007/978-981-99-2233-8_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2232-1

  • Online ISBN: 978-981-99-2233-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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