Uso de Lakehouses para um ambiente analítico espacial Big Data

Abstract

Digital transformation has driven the emergence of new ways of collecting and storing data. Initially, Data Warehouses and Data Lakes emerged to deal with complex analyses,high storage costs and the need for scalability. However,the growth of Big Data revealed limitations in these architectures, culminating in the development of solutions such as Data Lakehouses, which combine characteristics of both Data Lakes and Data Warehouses. Lakehouses offer a unified approach for dealing with diversity and large volumes of data while maintaining low costs, high analytical performance, flexibility and scalability. This work analyzes the limitations of current storage architectures, high lighting the support offered for Big Data and geospatial data. From this, a Lakehouse environment is built based on technologies such as Delta Lake, to explore data storage and analysis. It’s presented a real case study, where a t he Lake house environment simplemented to store and analyze geospatial data from public transportin four Brazilian cities. This work contributes to understanding trends in data architectures, especially in Spatial Big Data Analytics scenarios, facilitating the practical application of these concepts.