Publication
An architecture for an effective usage of data mining in business intelligence systems
| Summary: | Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented. |
|---|---|
| Main Authors: | Azevedo, Ana |
| Other Authors: | Santos, Manuel Filipe |
| Subject: | Knowledge discovery on databases Data mining Business intelligence Integration |
| Year: | 2009 |
| Country: | Portugal |
| Document type: | conference output |
| Access type: | open access |
| Associated institution: | Instituto Politécnico do Porto |
| Language: | English |
| Origin: | Repositório Científico do Instituto Politécnico do Porto |
| _version_ | 1868412647459782656 |
|---|---|
| author | Azevedo, Ana |
| author2 | Santos, Manuel Filipe |
| author2_role | author |
| author_facet | Azevedo, Ana Santos, Manuel Filipe |
| author_role | author |
| contributor_name_str_mv | REPOSITÓRIO P.PORTO |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Azevedo, Ana\",\"Person.identifier.orcid\":\"0000-0003-0882-3426\"},{\"Person.name\":\"Santos, Manuel Filipe\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | REPOSITÓRIO P.PORTO |
| datacite.creators.creator.creatorName.fl_str_mv | Azevedo, Ana Santos, Manuel Filipe |
| datacite.date.Accepted.fl_str_mv | 2009-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2012-08-06T11:35:35Z |
| datacite.date.embargoed.fl_str_mv | 2012-08-06T11:35:35Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Knowledge discovery on databases Data mining Business intelligence Integration |
| datacite.titles.title.fl_str_mv | An architecture for an effective usage of data mining in business intelligence systems |
| dc.contributor.none.fl_str_mv | REPOSITÓRIO P.PORTO |
| dc.creator.none.fl_str_mv | Azevedo, Ana Santos, Manuel Filipe |
| dc.date.Accepted.fl_str_mv | 2009-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2012-08-06T11:35:35Z |
| dc.date.embargoed.fl_str_mv | 2012-08-06T11:35:35Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.22/617 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Instituto Politécnico do Porto. Instituto Superior de Contabilidade e Administração do Porto |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Knowledge discovery on databases Data mining Business intelligence Integration |
| dc.title.fl_str_mv | An architecture for an effective usage of data mining in business intelligence systems |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_c94f |
| description | Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| fulltext.url.fl_str_mv | https://recipp.ipp.pt/bitstreams/09fd9031-8183-4421-8e5c-803e9a7c0017/download |
| id | recipp_ebefd32edbc16cecb1833025b7cdfd86 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.22/617 |
| instacron_str | recipp |
| institution | Instituto Politécnico do Porto |
| instname_str | Instituto Politécnico do Porto |
| language | eng |
| network_acronym_str | recipp |
| network_name_str | Repositório Científico do Instituto Politécnico do Porto |
| oai_identifier_str | oai:recipp.ipp.pt:10400.22/617 |
| organization_str_mv | urn:organizationAcronym:recipp |
| person_str_mv | Azevedo, Ana Azevedo, Ana https://www.ciencia-id.pt/D913-646F-CE08 D913-646F-CE08 http://orcid.org/0000-0003-0882-3426 0000-0003-0882-3426 Santos, Manuel Filipe |
| publishDate | 2009 |
| publisher.none.fl_str_mv | Instituto Politécnico do Porto. Instituto Superior de Contabilidade e Administração do Porto |
| reponame_str | Repositório Científico do Instituto Politécnico do Porto |
| repository_id_str | urn:repositoryAcronym:recipp |
| service_str_mv | urn:repositoryAcronym:recipp |
| spelling | engInstituto Politécnico do Porto. Instituto Superior de Contabilidade e Administração do PortoporBusiness Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.application/pdfporAn architecture for an effective usage of data mining in business intelligence systemsPersonalAzevedo, AnaDSpacehttp://dspace.org/items/d86b3493-7f70-42bd-a134-7724288f02b1DSpacehttp://dspace.org/items/d86b3493-7f70-42bd-a134-7724288f02b1AzevedoAnaCiência IDhttps://www.ciencia-id.ptD913-646F-CE08ORCIDhttp://orcid.org0000-0003-0882-3426Researcher IDhttps://www.researcherid.comH-3955-2011Scopus Author IDhttps://www.scopus.com25960566000Scopus Author IDhttps://www.scopus.com58021720500Santos, Manuel FilipeHostingInstitutionOrganizationalREPOSITÓRIO P.PORTOe-mailmailto:recipp@sc.ipp.ptrecipp@sc.ipp.pt2012-08-06T11:35:35Z20092009-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.22/617http://purl.org/coar/access_right/c_abf2open accessKnowledge discovery on databasesData miningBusiness intelligenceIntegration114648 bytesother research producthttp://purl.org/coar/resource_type/c_c94fconference objecthttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://recipp.ipp.pt/bitstreams/09fd9031-8183-4421-8e5c-803e9a7c0017/downloadKnowledge Management and Innovation in Advancing Economies: Analyses & Solutions13191325Marrocos |
| spellingShingle | An architecture for an effective usage of data mining in business intelligence systems Azevedo, Ana Knowledge discovery on databases Data mining Business intelligence Integration |
| status | SINGLETON |
| subject.fl_str_mv | Knowledge discovery on databases Data mining Business intelligence Integration |
| title | An architecture for an effective usage of data mining in business intelligence systems |
| title_full | An architecture for an effective usage of data mining in business intelligence systems |
| title_fullStr | An architecture for an effective usage of data mining in business intelligence systems |
| title_full_unstemmed | An architecture for an effective usage of data mining in business intelligence systems |
| title_short | An architecture for an effective usage of data mining in business intelligence systems |
| title_sort | An architecture for an effective usage of data mining in business intelligence systems |
| topic | Knowledge discovery on databases Data mining Business intelligence Integration |
| topic_facet | Knowledge discovery on databases Data mining Business intelligence Integration |
| url | http://hdl.handle.net/10400.22/617 |
| visible | 1 |