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English Information

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Authors
# Name
1 Beatriz Oliveira(beatrizfra@gmail.com)
2 Aline Valente(asoliveirav@gmail.com)
3 Edward Ribeiro(edwardribeiro@unb.br)
4 Marcio Victorino(mcvictorino@unb.br)
5 Maristela Holanda(mholanda@unb.br)

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Reference
# Reference
1 Cassavia, N., Dicosta, P., Masciari, E., and Sacca, D. (2014). Data preparation for tourist data big data warehousing. In International Conference on Data Management Technologies and Applications, pages 419–426. INSTICC, SciTePress.
2 Costa, E., Costa, C., and Santos, M. Y. (2017). Efficient big data modelling and organization for hadoop hive-based data warehouses. In Themistocleous, M. and Morabito, V., editors, European, Mediterranean and Middle Eastern Conference on Information Systems, pages 3–16. Springer International Publishing.
3 Di Tria, F., Lefons, E., and Tangorra, F. (2014). Design process for big data warehouses. In International Conference on Data Science and Advanced Analytics (DSAA), pages 512–518.
4 Jacobs, A. (2009). The pathologies of big data. Comm. of the ACM, 52(8):36–44.
5 Mohanty, S., Jagadeesh, M., and Srivatsa, H. (2013). Big data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics. Apress, 1st edition.
6 Rodrigues, M., Santos, M. Y., and Bernardino, J. (2019). Big data processing tools: An experimental performance evaluation. WIREs Data Mining and Knowledge Discovery, 9(2):e1297.
7 Sandoval, L. J. (2015). Design of business intelligence applications using big data technology. In 2015 IEEE Thirty Fifth Central American and Panama Convention (CONCAPAN XXXV), pages 1–6.
8 Santos, M. Y. and Costa, C. (2016). Data warehousing in big data: From multidimensional to tabular data models. In Ninth International C* Conference on Computer Science Software Engineering, pages 51–60. ACM.
9 Weintraub, G., Gudes, E., and Dolev, S. (2021). Needle in a haystack queries in cloud data lakes. In EDBT/ICDT Workshops. CEUR-WS.org.