Publicação
Using data vault 2.0 in the banking industry
| Resumo: | Organizations increasingly recognize data as a critical resource, demanding effective storage and processing methods to handle exponentially growing volumes of data. This is particularly pertinent in the banking industry, characterized by rapidly changing business requirements and heavy regulatory measures. This thesis investigates the application of the Data Vault 2.0 Enterprise Data Warehouse (EDW) methodology within the banking sector, an alternative to traditional Kimball and Inmon data warehouses, characterized by its flexibility, scalability, and its ability to adapt to new business requirements. This study particularly focuses on the potential of integrating data sourced from a data lake, a centralized repository capable of storing massive volumes of structurally diverse data, to amplify the potential of this solution. This research, conducted in collaboration with a leading Portuguese bank servicing three million customers, involved the creation of a Data Vault model using the bank’s customer and current account data. The model’s ability to accurately reflect the business logic and adapt to real-world requirements was demonstrated, and subsequently evaluated by experienced professionals within the organization. The results reveal significant potential for the implementation of a Data Vault 2.0 EDW in conjunction with a data lake in the banking industry, as a scalable, efficient system that can realistically be adopted and excel in an enterprise setting. |
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| Autores principais: | Hipólito, Diogo Filipe Farinha |
| Assunto: | Data Vault 2.0 Data Lake Data Warehouse Data management Data architecture |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | Organizations increasingly recognize data as a critical resource, demanding effective storage and processing methods to handle exponentially growing volumes of data. This is particularly pertinent in the banking industry, characterized by rapidly changing business requirements and heavy regulatory measures. This thesis investigates the application of the Data Vault 2.0 Enterprise Data Warehouse (EDW) methodology within the banking sector, an alternative to traditional Kimball and Inmon data warehouses, characterized by its flexibility, scalability, and its ability to adapt to new business requirements. This study particularly focuses on the potential of integrating data sourced from a data lake, a centralized repository capable of storing massive volumes of structurally diverse data, to amplify the potential of this solution. This research, conducted in collaboration with a leading Portuguese bank servicing three million customers, involved the creation of a Data Vault model using the bank’s customer and current account data. The model’s ability to accurately reflect the business logic and adapt to real-world requirements was demonstrated, and subsequently evaluated by experienced professionals within the organization. The results reveal significant potential for the implementation of a Data Vault 2.0 EDW in conjunction with a data lake in the banking industry, as a scalable, efficient system that can realistically be adopted and excel in an enterprise setting. |
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