Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/6906
Título: Big data warehouse framework for smart revenue management
Autor: Ramos, Célia M. Q.
Correia, Marisol B.
Rodrigues, J. M. F.
Martins, Daniel
Serra, Francisco
Palavras-chave: Revenue management
Data warehouse
Big data
Business intelligence
Semantic web
Tourism
Hospitality
Marketing
Data: 2015
Editora: WSEAS Press
Citação: Correia, Marisol de Brito. Big Data Warehouse Framework for Smart Revenue Management, Trabalho apresentado em NAUN Int. Conf. on Management, Marketing, Tourism, Retail, Finance and Computer Applications (MATREFC '15), In 3rd NAUN Int. Conf. on Management, Marketing, Tourism, Retail, Finance and Computer Applications (MATREFC '15), Tenerife, 2015.
Resumo: Revenue Management’s most cited definitions is probably “to sell the right accommodation to the right customer, at the right time and the right price, with optimal satisfaction for customers and hoteliers”. Smart Revenue Management (SRM) is a project, which aims the development of smart automatic techniques for an efficient optimization of occupancy and rates of hotel accommodations, commonly referred to, as revenue management. One of the objectives of this project is to demonstrate that the collection of Big Data, followed by an appropriate assembly of functionalities, will make possible to generate a Data Warehouse necessary to produce high quality business intelligence and analytics. This will be achieved through the collection of data extracted from a variety of sources, including from the web. This paper proposes a three stage framework to develop the Big Data Warehouse for the SRM. Namely, the compilation of all available information, in the present case, it was focus only the extraction of information from the web by a web crawler – raw data. The storing of that raw data in a primary NoSQL database, and from that data the conception of a set of functionalities, rules, principles and semantics to select, combine and store in a secondary relational database the meaningful information for the Revenue Management (Big Data Warehouse). The last stage will be the principal focus of the paper. In this context, clues will also be giving how to compile information for Business Intelligence. All these functionalities contribute to a holistic framework that, in the future, will make it possible to anticipate customers and competitor’s behavior, fundamental elements to fulfill the Revenue Management
Peer review: yes
URI: http://hdl.handle.net/10400.1/6906
ISBN: 978-1-61804-280-4
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