Building a business intelligence dashboard for a Lebanese company

Gerard Najem; Jesualdo Cerqueira Fernandes

doi:10.5585/iptec.v11i1.24603

Autores

Gerard Najem ISEG - Lisbon School of Economics and Management https://orcid.org/0009-0002-1004-9177
Jesualdo Cerqueira Fernandes ADVANCE ISEG - Lisbon School of Economics and Management https://orcid.org/0000-0001-7131-4574

DOI:

https://doi.org/10.5585/iptec.v11i1.24603

Palavras-chave:

Business Intelligence, Dashboards, Data, ETL, Modelling.

Resumo

Neste estudo, desenvolvemos um dashboard de Business Intelligence para uma empresa libanesa para melhorar sua gestão financeira. O desenvolvimento envolveu a integração dos dados disponíveis numa base de dados física, recorrendo a Python e PostgreSQL. A partir dessa base de dados, geramos um dashboard com o Power BI para visualizar e analisar os valores de receita. O resultado ajudou a empresa a obter insights sobre o desempenho dos seus negócios, otimizar a receita e o lucro e identificar problemas de entrada de dados que podem afetar os resultados. O dashboard também fornece uma base para futuras integrações e análises de novos dados.

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Biografia do Autor

Jesualdo Cerqueira Fernandes, ADVANCE ISEG - Lisbon School of Economics and Management

Assistent Professor of Information Systems

Department of Management

Referências

Bray T (2011) The role of business intelligence dashboards in financial management. Credit Control 32 (5/6): 29–33

Breslin J G (2019) Developing an organizational data strategy. J Bus Manag 24(1): 35-42 https://doi.org/10.3390/app11073186

Cukier K (2013) Data, data everywhere: A special report on managing information. The Economist 25 https://doi.org/10.4324/9781315856469

Davenport T H, and Harris J G (2007) Competing on analytics: The new science of winning. Harvard Business Press, https://doi.org/10.5860/choice.44-6322

Fernández A (2020) El papel del Big Data en el reporting y la toma de decisiones. Contabilidad y Direccion 31, 21–36

Gandomi A, and Haider M (2015) Beyond the hype: Big data concepts, methods, and analytics. Inter J Info Manag 35(2), 137–144 https://doi:10.1016/j.ijinfomgt.2014.10.007

Gao J, and Ren G (2020) Social media data analytics: An overview. IEEE Transac Compu Social Systems 7(6): 1621–1633

García-Sánchez F, Pérez-González D, and Pavón-Mariño P (2018) A survey of data modeling techniques for big data. Info Systems 73: 1–19

Hernández-Orallo J, Ramírez-Quintana M J, and Flach P A (2020) Explainable AI: Interpreting, explaining and visualizing deep learning. Springer https://doi.org/10.1007/978-3-030-28954-6

Kim S H, and LeeJ N (2012) The impact of organizational context and information technology on employee knowledge-sharing capabilities. Public Admin Rev 72(4), 527–536 https://doi:10.1111/j.1540-6210.2006.00595.x

Lenzerini M (2002) Data integration: A theoretical perspective. Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems 233–246 https://doi:10.1145/543613.543644

Li X, Huang J, Wang L, and Lu X (2018) Big data analytics in supply chain management: A comprehensive overview and future directions. Computers Indus Engineer 116: 299–316 https://doi.org/10.3390/bdcc6010017

Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, and Byers A H (2011) Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Instit: 1–156

Popescu S (2012) Business intelligence solutions - A way of general improvement of efficiency and effectiveness. Rev Inter Compar Manag / Revista de Manag Comparat Inter 13(1): 88–95

Wieder B, Ossimitz M-L, and Chamoni P (2012) The impact of business intelligence tools on performance: A user satisfaction paradox? Inter J Econ Sciences and Applied Res 5(3): 7–32

Wu X, Zhu X, Wu G Q, and Ding W (2021) Data mining with big data. IEEE Trans Know Data Engineer 33(5): 1855–¬1878 https://doi.org/10.1109/TKDE.2013.109

Younus A, and Qureshi M A (2021) Data analytics for business decision making: A comparative study of regression techniques. In Proceedings of the 4th International Conference on Future Networks and Distributed Systems (pp 229–241)