Utilizing an airline data warehouse for website data analytics: A conceptual design

Ravnesh Kumar; Kunal Kumar

doi:10.1007/978-981-99-2233-8_19

Utilizing an airline data warehouse for website data analytics: A conceptual design

Ravnesh Kumar
, Kunal Kumar

Computing, Mathematics and Engineering

University of Fiji

Research output: Book chapter/Published conference paper › Conference paper › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Big Data Intelligence and Computing
Subtitle of host publication	International Conference, DataCom 2022 Denarau Island, Fiji, December 8–10, 2022 Proceedings
Publisher	Springer
Pages	259-274
Number of pages	16
Volume	13864
ISBN (Electronic)	9789819922338
ISBN (Print)	9789819922321
DOIs	https://doi.org/10.1007/978-981-99-2233-8_19
Publication status	E-pub ahead of print - May 2023
Event	International Conference on Big Data Intelligence and Computing 2022: DataCom 2022 - Sheraton Fiji Golf and Beach Resort, Denarau Island, Fiji Duration: 08 Dec 2022 → 10 Dec 2022 https://web.archive.org/web/20221204093527/https://www.datacom-ieee.org/ https://link.springer.com/book/10.1007/978-981-99-2233-8 (Proceedings) http://wikicfp.com/cfp/servlet/event.showcfp?eventid=169450 (Call for papers)

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	13864
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Big Data Intelligence and Computing 2022
Country/Territory	Fiji
City	Denarau Island
Period	08/12/22 → 10/12/22
Other	Big data is a rapidly expanding research area spanning the fields of computer science and information management, and has become a ubiquitous term in understanding and solving complex problems in different disciplinary fields such as engineering, applied mathematics, medicine, computational biology, healthcare, social networks, finance, business, government, education, transportation and telecommunications. The goal of the 2022 International Conference on Big Data Intelligence and Computing (DataCom 2022) is to establish an international forum for engineers and scientists to present their ideas and experiences in the fields of Big Data intelligence and computing. DataCom 2022 welcomes paper submissions on innovative work from researchers in academia, industry and government describing original research work in Big Data. DataCom 2022 will be held on December 08-10, 2022, co-located with FCP 2022 in Sheraton Fiji Golf & Beach Resort, Denarau Island, Fiji
Internet address	https://web.archive.org/web/20221204093527/https://www.datacom-ieee.org/ https://link.springer.com/book/10.1007/978-981-99-2233-8 (Proceedings) http://wikicfp.com/cfp/servlet/event.showcfp?eventid=169450 (Call for papers)

Access to Document

10.1007/978-981-99-2233-8_19

Cite this

Kumar, R., & Kumar, K. (2023). Utilizing an airline data warehouse for website data analytics: A conceptual design. In Big Data Intelligence and Computing: International Conference, DataCom 2022 Denarau Island, Fiji, December 8–10, 2022 Proceedings (Vol. 13864, pp. 259-274). (Lecture Notes in Computer Science; Vol. 13864). Springer. Advance online publication. https://doi.org/10.1007/978-981-99-2233-8_19

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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{\textquoteright}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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url = "https://web.archive.org/web/20221204093527/https://www.datacom-ieee.org/, https://link.springer.com/book/10.1007/978-981-99-2233-8, http://wikicfp.com/cfp/servlet/event.showcfp?eventid=169450",

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Kumar, R & Kumar, K 2023, Utilizing an airline data warehouse for website data analytics: A conceptual design. in Big Data Intelligence and Computing: International Conference, DataCom 2022 Denarau Island, Fiji, December 8–10, 2022 Proceedings. vol. 13864, Lecture Notes in Computer Science, vol. 13864, Springer, pp. 259-274, International Conference on Big Data Intelligence and Computing 2022, Denarau Island, Fiji, 08/12/22. https://doi.org/10.1007/978-981-99-2233-8_19

Utilizing an airline data warehouse for website data analytics: A conceptual design. / Kumar, Ravnesh; Kumar, Kunal.
Big Data Intelligence and Computing: International Conference, DataCom 2022 Denarau Island, Fiji, December 8–10, 2022 Proceedings. Vol. 13864 Springer, 2023. p. 259-274 (Lecture Notes in Computer Science; Vol. 13864).

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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T1 - Utilizing an airline data warehouse for website data analytics

T2 - International Conference on Big Data Intelligence and Computing 2022

AU - Kumar, Ravnesh

AU - Kumar, Kunal

PY - 2023/5

Y1 - 2023/5

N2 - 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.

AB - 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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DO - 10.1007/978-981-99-2233-8_19

M3 - Conference paper

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VL - 13864

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BT - Big Data Intelligence and Computing

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Y2 - 8 December 2022 through 10 December 2022

ER -

Utilizing an airline data warehouse for website data analytics: A conceptual design

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