Implementação de um data lake em uma empresa de agenciamento de carga utilizando tecnologias AWS: um estudo de caso

Abstract

Freight forwarding is an essential activity in international trade, responsible for organizing and coordinating the transportation of goods between different countries. With the increase in globalization, the efficient management of large volumes of import and export transaction data has become crucial. This work addresses the problem of data analysis difficulty in the freight forwarding sector. The objective is to explore the implementation of a data lake using AWS (Amazon Web Services) technologies to centralize, process, and analyze these data. The methodology involved a practical case study where tools such as S3, Lambda, Glue Catalog, and Athena were used for data ingestion, transformation, and analysis. The results demonstrated that implementing a data lake can significantly improve the operational efficiency and analytical capacity of the company, providing valuable insights and facilitating informed decision-making. The proposed approach also offers a replicable model for other companies in the sector, highlighting the relevance of data lake technologies in managing complex data.