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Enhancing decision-making through BI automation

2026-08-02Comunicação em conferência Acesso aberto
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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg04:Educação de Qualidade
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorRibeiro, Hélder
dc.contributor.authorGonçalves, Carlos A.
dc.contributor.authorBENEDITA CAMPOS NEVES MALHEIRO, MARIA
dc.date.accessioned2026-09-02T08:19:40Z
dc.date.available2026-09-02T08:19:40Z
dc.date.issued2026-08-02
dc.description.abstractEvery second, large volumes of data are generated which, if not properly interpreted, can lead to wrong decisions and undesirable consequences. Automating and optimising information processing enables faster handling and supports timely, informed decision-making. With the evolution of Business Intelligence tools, adopting data-driven solutions is essential for organisational competitiveness. This work tackles real-time management and analysis of strategic and operational industrial data through the design and development of the Unified Performance Metrics dashboard, which consolidates strategic information of internal business units via key metrics, and the improvement of the existing human resources dashboard. The system integrates a Power BI front-end with a Python- and SQL-based back-end for automation and the extract, transform, and load process. The dashboards were successfully evaluated, approved, and deployed. By automating strategic and operational analyses, the dashboards effectively replaced inefficient manual error-prone procedures, demonstrating clear operational advantages.eng
dc.identifier.citationRibeiro, H., Gonçalves, C.A., Malheiro, B. (2027). Enhancing Decision-Making Through BI Automation. In: Rocha, A., Adeli, H., Moreira, F. (eds) Recent Trends and Challenges in Information Systems and Technologies. WorldCIST 2026. Lecture Notes in Networks and Systems, vol 2092. Springer, Cham, 538-548. https://doi.org/10.1007/978-3-032-32023-0_44
dc.identifier.doi10.1007/978-3-032-32023-0_44
dc.identifier.urihttp://hdl.handle.net/10400.22/32663
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature Switzerland
dc.relationINESC TEC - INESC Technology and Science
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-032-32023-0_44
dc.relation.ispartofLecture Notes in Networks and Systems
dc.relation.ispartofRecent Trends and Challenges in Information Systems and Technologies
dc.relation.ispartofseriesLecture Notes in Networks and Systems
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectBusiness intelligence
dc.subjectdecision-making
dc.subjectdashboards
dc.subjectextract-transform-load
dc.subjectinformation management
dc.subjectmetrics
dc.subjectPower BI
dc.subjectdata automation workflow
dc.titleEnhancing decision-making through BI automationeng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardNumberUID/EEA/50014/2013
oaire.awardTitleINESC TEC - INESC Technology and Science
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F50014%2F2013/PT
oaire.citation.conferenceDate2026-03-31
oaire.citation.conferencePlaceMadeira, Portugal
oaire.citation.endPage548
oaire.citation.startPage538
oaire.citation.titleWorldCIST 2026 - 14th World Conference on Information Systems and Technologies
oaire.citation.volume2092
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.familyNameBENEDITA CAMPOS NEVES MALHEIRO
person.givenNameMARIA
person.identifier.ciencia-id7A15-08FC-4430
person.identifier.orcid0000-0001-9083-4292
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublicationbabd4fda-654a-4b59-952d-6113eebbb308
relation.isAuthorOfPublication.latestForDiscoverybabd4fda-654a-4b59-952d-6113eebbb308
relation.isProjectOfPublication83dccc11-0e61-4cb1-b1a7-adad289c49a3
relation.isProjectOfPublication.latestForDiscovery83dccc11-0e61-4cb1-b1a7-adad289c49a3

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