Publicação
Cloud data warehousing solution in the banking sector
| Resumo: | The Covid-19 pandemic brought about many changes in the business world, and one of the most significant was the accelerated adoption of digital technologies. Commercial banks were no exception, launching several IT projects to support remote work and digital customer experiences. However, this surge in IT projects led to an overload of project management issues. With limited resources and competing priorities, project managers struggled to keep up with the increased workload. To address this problem, banks searched for means to store and analyze important data that would allow them to improve their resource allocation and operational efficiency. Some of Portugal’s largest commercial banks substantially invested in data warehousing and analysis solutions to achieve these goals. The present study is a result of these investments and seeks to create a robust data warehousing solution in which data can be safely stored and develop a business intelligence report for data analysis purposes. The objective of this project is to combine these two components into a decision support system capable of providing up-to-date and accurate information that empowers the bank’s managers to make informed business decisions. This data warehousing solution is deployed on the cloud and involves the creation of an architecture that can handle massive amounts of data while remaining highly scalable. This architecture leverages the Data Lakehouse concept with Kimball's Data Bus principles to achieve its scalability and efficiency. Although some concerns were raised regarding its dependencies on external sources, the solution was implemented successfully and proved to be effective in this specific business context. |
|---|---|
| Autores principais: | Silvestre, João Diogo Miguel |
| Assunto: | Data Lakehouse Data Warehouse Business Intelligence Cloud Computing |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1866809446210994176 |
|---|---|
| author | Silvestre, João Diogo Miguel |
| author_facet | Silvestre, João Diogo Miguel |
| author_role | author |
| contributor_name_str_mv | Costa, Carlos Miguel, Rui Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Silvestre, João Diogo Miguel\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Costa, Carlos Miguel, Rui Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Silvestre, João Diogo Miguel |
| datacite.date.Accepted.fl_str_mv | 2023-03-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-07-28T09:45:13Z |
| datacite.date.embargoed.fl_str_mv | 2023-07-28T09:45:13Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Data Lakehouse Data Warehouse Business Intelligence Cloud Computing |
| datacite.titles.title.fl_str_mv | Cloud data warehousing solution in the banking sector |
| dc.contributor.none.fl_str_mv | Costa, Carlos Miguel, Rui Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Silvestre, João Diogo Miguel |
| dc.date.Accepted.fl_str_mv | 2023-03-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-07-28T09:45:13Z |
| dc.date.embargoed.fl_str_mv | 2023-07-28T09:45:13Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.5/28059 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Instituto Superior de Economia e Gestão |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Data Lakehouse Data Warehouse Business Intelligence Cloud Computing |
| dc.title.fl_str_mv | Cloud data warehousing solution in the banking sector |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | The Covid-19 pandemic brought about many changes in the business world, and one of the most significant was the accelerated adoption of digital technologies. Commercial banks were no exception, launching several IT projects to support remote work and digital customer experiences. However, this surge in IT projects led to an overload of project management issues. With limited resources and competing priorities, project managers struggled to keep up with the increased workload. To address this problem, banks searched for means to store and analyze important data that would allow them to improve their resource allocation and operational efficiency. Some of Portugal’s largest commercial banks substantially invested in data warehousing and analysis solutions to achieve these goals. The present study is a result of these investments and seeks to create a robust data warehousing solution in which data can be safely stored and develop a business intelligence report for data analysis purposes. The objective of this project is to combine these two components into a decision support system capable of providing up-to-date and accurate information that empowers the bank’s managers to make informed business decisions. This data warehousing solution is deployed on the cloud and involves the creation of an architecture that can handle massive amounts of data while remaining highly scalable. This architecture leverages the Data Lakehouse concept with Kimball's Data Bus principles to achieve its scalability and efficiency. Although some concerns were raised regarding its dependencies on external sources, the solution was implemented successfully and proved to be effective in this specific business context. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/437a0745-06be-42ac-bdcd-2a4c8a899e1b/download |
| id | ul_732a37b5bafebb5ec7fb2eba064ce83a |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.5/28059 |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | eng |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10400.5/28059 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Silvestre, João Diogo Miguel |
| publishDate | 2023 |
| publisher.none.fl_str_mv | Instituto Superior de Economia e Gestão |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | engInstituto Superior de Economia e Gestãopt_PTThe Covid-19 pandemic brought about many changes in the business world, and one of the most significant was the accelerated adoption of digital technologies. Commercial banks were no exception, launching several IT projects to support remote work and digital customer experiences. However, this surge in IT projects led to an overload of project management issues. With limited resources and competing priorities, project managers struggled to keep up with the increased workload. To address this problem, banks searched for means to store and analyze important data that would allow them to improve their resource allocation and operational efficiency. Some of Portugal’s largest commercial banks substantially invested in data warehousing and analysis solutions to achieve these goals. The present study is a result of these investments and seeks to create a robust data warehousing solution in which data can be safely stored and develop a business intelligence report for data analysis purposes. The objective of this project is to combine these two components into a decision support system capable of providing up-to-date and accurate information that empowers the bank’s managers to make informed business decisions. This data warehousing solution is deployed on the cloud and involves the creation of an architecture that can handle massive amounts of data while remaining highly scalable. This architecture leverages the Data Lakehouse concept with Kimball's Data Bus principles to achieve its scalability and efficiency. Although some concerns were raised regarding its dependencies on external sources, the solution was implemented successfully and proved to be effective in this specific business context.application/pdfpt_PTCloud data warehousing solution in the banking sectorSilvestre, João Diogo MiguelCosta, CarlosMiguel, RuiHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.pt2023-07-28T09:45:13Z2023-032023-03-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/28059http://purl.org/coar/access_right/c_abf2open accessData LakehouseData WarehouseBusiness IntelligenceCloud Computing2733928 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/437a0745-06be-42ac-bdcd-2a4c8a899e1b/download |
| spellingShingle | Cloud data warehousing solution in the banking sector Silvestre, João Diogo Miguel Data Lakehouse Data Warehouse Business Intelligence Cloud Computing |
| status | SINGLETON |
| subject.fl_str_mv | Data Lakehouse Data Warehouse Business Intelligence Cloud Computing |
| title | Cloud data warehousing solution in the banking sector |
| title_full | Cloud data warehousing solution in the banking sector |
| title_fullStr | Cloud data warehousing solution in the banking sector |
| title_full_unstemmed | Cloud data warehousing solution in the banking sector |
| title_short | Cloud data warehousing solution in the banking sector |
| title_sort | Cloud data warehousing solution in the banking sector |
| topic | Data Lakehouse Data Warehouse Business Intelligence Cloud Computing |
| topic_facet | Data Lakehouse Data Warehouse Business Intelligence Cloud Computing |
| url | http://hdl.handle.net/10400.5/28059 |
| visible | 1 |