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An Evaluation of How Big-Data and Data Warehouses Improve Business Intelligence Decision Making

2020Conference object Restricted access
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dc.contributor.authorMartins, Anthony
dc.contributor.authorMartins, Pedro
dc.contributor.authorCaldeira, Filipe
dc.contributor.authorSá, Filipe
dc.contributor.editorRocha, {\'Aen_US
dc.date.accessioned2023-07-04T10:40:14Z
dc.date.available2023-07-04T10:40:14Z
dc.date.issued2020
dc.date.updated2023-06-14T14:45:07Z
dc.description.abstractAnalyze and understand how to combine data warehouse with business intelligence tools, and other useful information or tools to visualize KPIs are critical factors in achieving the goal of raising competencies and business results of an organization. This article reviews data warehouse concepts and their appropriate use in business intelligence projects with a focus on large amounts of information. Nowadays, data volume is more significant and critical, and proper data analysis is essential for a successful project. From importing data to displaying results, there are crucial tasks such as extracting information, transforming it analyzing, and storing data for later querying. This work contributes with the proposition of a Big Data Business Intelligence architecture for an efficiently BI platform and the explanation of each step in creating a Data Warehouse and how data transformation is designed to provide useful and valuable information. To make valuable information useful, Business Intelligence tools are presented and evaluates, contributing to the continuous improvement of business results.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-030-45688-7_61pt_PT
dc.identifier.eid2-s2.0-85085500703
dc.identifier.isbn978-3-030-45688-7
dc.identifier.issn21945365 21945357
dc.identifier.slugcv-prod-3079547
dc.identifier.urihttp://hdl.handle.net/10400.19/7855
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer International Publishingpt_PT
dc.subjectData Warehousept_PT
dc.subject· Big Datapt_PT
dc.subjectData Mart ·pt_PT
dc.subjectBusiness Intelligencept_PT
dc.subjectOLAPpt_PT
dc.subjectETLpt_PT
dc.subjectPower BIpt_PT
dc.subjectAnalytical methodspt_PT
dc.titleAn Evaluation of How Big-Data and Data Warehouses Improve Business Intelligence Decision Makingpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.endPage619pt_PT
oaire.citation.startPage609pt_PT
oaire.citation.titleWorldCIST 2020pt_PT
person.familyNameCaldeira
person.familyNameSá
person.givenNameFilipe
person.givenNameFilipe
person.identifierlXPmBvYAAAAJ
person.identifierR-00H-E4X
person.identifier.ciencia-idCB11-8109-AB1D
person.identifier.ciencia-id791E-0243-634F
person.identifier.orcid0000-0001-7558-2330
person.identifier.orcid0000-0002-7846-8397
person.identifier.scopus-author-id36023210300
person.identifier.scopus-author-id8447524700
rcaap.cv.cienciaidCB11-8109-AB1D | Filipe Caldeira
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicatione845705e-5b0b-4f70-9c53-c472ffd768d1
relation.isAuthorOfPublication9fb8350d-65a7-4170-b28f-cc60c70c0bb2
relation.isAuthorOfPublication.latestForDiscovery9fb8350d-65a7-4170-b28f-cc60c70c0bb2

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