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Big data warehouse framework for smart revenue management

2015Journal article Open access
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dc.contributor.authorRamos, Célia M. Q.
dc.contributor.authorCorreia, Marisol B.
dc.contributor.authorRodrigues, J. M. F.
dc.contributor.authorMartins, Daniel
dc.contributor.authorSerra, Francisco
dc.date.accessioned2015-10-15T13:30:20Z
dc.date.available2015-10-15T13:30:20Z
dc.date.issued2015
dc.date.updated2015-10-12T17:20:11Z
dc.description.abstractRevenue 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 Managementpt_PT
dc.identifier978-1-61804-280-4en_US
dc.identifier.citationCorreia, 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.pt_PT
dc.identifier.isbn978-1-61804-280-4
dc.identifier.otherAUT: MCO00732; CMR00726; AUT: JRO00913; FSE00957;
dc.identifier.urihttp://hdl.handle.net/10400.1/6906
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherWSEAS Presspt_PT
dc.subjectRevenue managementpt_PT
dc.subjectData warehousept_PT
dc.subjectBig datapt_PT
dc.subjectBusiness intelligencept_PT
dc.subjectSemantic webpt_PT
dc.subjectTourismpt_PT
dc.subjectHospitalitypt_PT
dc.subjectMarketingpt_PT
dc.titleBig data warehouse framework for smart revenue managementpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceTenerife, Canary Islands, Spainpt_PT
oaire.citation.endPage22pt_PT
oaire.citation.startPage13pt_PT
oaire.citation.titleAdvances in Environmental Science and Energy Planningpt_PT
person.familyNameRamos
person.familyNameCorreia
person.familyNameRodrigues
person.familyNameSerra
person.givenNameCelia
person.givenNameMarisol B.
person.givenNameJoao
person.givenNameFrancisco
person.identifier0000000428330706
person.identifier.ciencia-idB917-D015-C2EF
person.identifier.ciencia-idFE15-819A-4535
person.identifier.ciencia-id8A19-98F7-9914
person.identifier.ciencia-id4D1C-9D66-8D99
person.identifier.orcid0000-0002-3413-4897
person.identifier.orcid0000-0002-1788-6114
person.identifier.orcid0000-0002-3562-6025
person.identifier.orcid0000-0002-8461-5162
person.identifier.ridC-5119-2012
person.identifier.scopus-author-id35073165500
person.identifier.scopus-author-id55333058000
person.identifier.scopus-author-id55807461600
person.identifier.scopus-author-id56290841200
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication683ba85b-459c-4789-a4ff-a4e2a904b295
relation.isAuthorOfPublication22775c38-a6c8-4162-9ac0-c1941fbf693c
relation.isAuthorOfPublication.latestForDiscovery22775c38-a6c8-4162-9ac0-c1941fbf693c

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