Assessing Data Quality Inconsistencies in Brazilian Governmental Data

Abstract

In recent years, vast volumes of data are constantly being made available on the Web, and they have been increasingly used as decision support in different contexts. However, for these decisions to be more assertive and reliable, it is necessary to ensure data quality. Although there are several definitions for this area, it is a consensus that data quality is always associated with a specific context. This work aims to analyze data quality in a data warehouse with governmental information of the Brazilian state of Minas Gerais. We first present a brief comparison of eight open-source data quality tools and then choose the Great Expectations tool for analyzing such data in two real applications: public bids and public expenditure. Our analyses show that the chosen tool has relevant characteristics to generate good data quality indicators to reveal data quality issues that may directly impact the construction of final applications using such data.