Keita, Moussa (2022): Modéliser un Data Warehouse d’Entreprise: Cas du Schéma en Etoile, du Modèle Normalisé et du Data Vault.
Preview |
PDF
MPRA_paper_112693.pdf Download (2MB) | Preview |
Abstract
In recent years, Data Warehouses have become essential tools for companies to deal with decision-making and strategic issues related to Big Data. The purpose of this document is to present three main approaches to Data Warehouse modeling, namely the star schema, the normalized model 3NF and the Data Vault model.
Item Type: | MPRA Paper |
---|---|
Original Title: | Modéliser un Data Warehouse d’Entreprise: Cas du Schéma en Etoile, du Modèle Normalisé et du Data Vault |
English Title: | Modeling an Enterprise Data Warehouse: Case of the Star Schema, the Normalized Model and the Data Vault |
Language: | French |
Keywords: | Data Ware house, modèle en étoile, modèle normalisé 3NF, Data Vault, Business Vault, PIT, Bridge |
Subjects: | C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs |
Item ID: | 112693 |
Depositing User: | Moussa keita |
Date Deposited: | 10 Apr 2022 11:22 |
Last Modified: | 31 Oct 2023 12:58 |
References: | Alrehamy, H. H. et C. Walker (2015). Personal Data Lake With Data Gravity Pull. In IEEE 5th International Conference on Big Data and Cloud Computing (BDCloud 2015), Dalian, China, pp. 160–167. Dixon, J. (2010). Pentaho, Hadoop and Data Lakes. https ://jamesdixon.wordpress.com/2010/10/14/pentaho-hadoop-and-data-lakes/. Graziano Kent (2015), The Business Data Vault, accessible en ligne ici Linstedt D. (2002), Data Vault Series, The Data Administration Newsletter Linstedt, D. (2011). Super Charge your Data Warehouse : Invaluable Data Modeling Rules to Implement Your Data Vault. CreateSpace Independent Publishing. Miloslavskaya, N. et A. Tolstoy (2016). Big Data, Fast Data and Data Lake Concepts. Procedia Computer Science 88, 300–305. Stein, B. et A. Morrison (2014). The enterprise data lake : Better integration and deeper analytics. Technology Forecast, 1. http ://www.pwc.com/us/en/technology-forecast/2014/cloudcomputing/assets/pdf/pwc-technology-forecast-data-lakes.pdf. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/112693 |