Comparing to Previous Runs

Overview

Comparing to previous runs provide valuable insights into changes and anomalies in your data over time. This process can be performed in two ways: comparing to a previous test result or comparing to a previous profile result.

Significance of Comparing to Previous Runs

Comparing data to previous runs helps in data trend analysis, anomaly detection, and monitoring data volatility over time. This feature is essential for the following reasons:

• Trend Analysis: By comparing current data to previous runs, you can detect trends and patterns in your data. This is important in making data-driven decisions and forecasts.
• Anomaly Detection: Comparing to previous runs can help detect anomalies that would otherwise go unnoticed. Spotting these early can be crucial in maintaining the integrity of your data.
• Data Volatility Monitoring: This feature allows you to monitor changes in your data over time especially regarding how the database processes new data additions and updates.

Comparing to a Previous Test Result

Comparing to a previous test result allows you to select what to compare the results by and define the length of the test execution coverage history. The coverage history can be specified in terms of the number of days, weeks, or runs.

Comparing to a Previous Profile Result

Comparing to a previous profile result lets you select the Data Source and an object from which to retrieve profile data information. This data is then compared to the test data set.

Conclusion

Comparing to previous runs can increase the effectiveness of your data quality assurance processes. By leveraging this ability to track changes over time, monitor the consistency of your data, identify trends, spot anomalies quickly, and ensure your data's overall quality and integrity.