Automated Monitoring (data quality)

≡Description

Automated monitoring refers to the use of automated systems to continuously supervise data quality across various applications and technological environments. This approach enables organizations to detect anomalies, inconsistencies, and data quality issues in real time, which is crucial for informed decision-making. Through algorithms and analytical tools, automated monitoring can identify patterns and trends in data, facilitating the early detection of issues before they escalate into crises. The main characteristics of this type of monitoring include the ability to perform real-time analysis, integration with various data sources, and the generation of automated alerts when irregularities are detected. The relevance of automated monitoring lies in its ability to improve data trust, optimize processes, and reduce operational costs, allowing companies to focus on innovation and growth rather than on managing data quality issues.