Publicação
Hybrid Data Warehouses: A Cloud and On-Premises Approach
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | Neto, Miguel de Castro Simões Ferreira | |
| dc.contributor.advisor | Jardim, João Bruno Morais de Sousa | |
| dc.contributor.author | Severiano, Renato Alexandre Pires | |
| dc.date.accessioned | 2024-03-13T10:22:26Z | |
| dc.date.available | 2024-03-13T10:22:26Z | |
| dc.date.issued | 2024-02-01 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence | pt_PT |
| dc.description.abstract | This project investigates the crucial role of data warehouses in the decision-making processes of business analysts, focusing on the transition from traditional to cloud-based environments in the face of Big Data challenges. The spotlight is on hybrid data warehouses, bridging on-premises and cloud-based solutions, aiming to understand their architectures, motivations, technical approaches, and associated benefits and drawbacks. In order to achieve the goal of this project, a Hybrid Data Warehouse that orchestrates on-premises and cloud systems with dimension and fact tables available in both locations was conceptualized. In this project were used Microsoft Tools, such as SQL Server, Visual Studio and the Azure Cloud. Additionally, the project delves into reasons for organizations adopting hybrid data warehouses, including supporting hybrid data architecture, enhancing data accessibility, agility, and cost reduction, always considering the limitations of the scope, regarding the comparability to similar solutions and applicability in real-life scenarios. Despite the limitations, while serving as a starting point, the project positions itself as a foundation for future research and development. It anticipates inspiring further exploration, optimization, and advancements in hybrid data warehouse architectures, contributing to the evolving landscape of data management in the digital era. | pt_PT |
| dc.identifier.tid | 203544340 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/164843 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Business intelligence | pt_PT |
| dc.subject | Hybrid data warehouses | pt_PT |
| dc.subject | On-premises | pt_PT |
| dc.subject | Cloud architecture | pt_PT |
| dc.subject | Dimension and fact tables | pt_PT |
| dc.subject | ETL (Extract | pt_PT |
| dc.subject | Transform | pt_PT |
| dc.subject | Load) | pt_PT |
| dc.subject | Replication | pt_PT |
| dc.subject | SDG 9 - Industry, innovation and infrastructure | pt_PT |
| dc.title | Hybrid Data Warehouses: A Cloud and On-Premises Approach | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Gestão de Informação, especialização em Gestão do Conhecimento e Inteligência de Negócio (Business Intelligence) | pt_PT |