🎯 Definicja
🔑 Kluczowe punkty
📚 Szczegółowe wyjaśnienie
💡 Przykład zastosowania
📌 Źródła
👽 Brudnopis
Anomaly detection discovers any inconsistencies or irregularities in the data.
- Anomaly detection is applied in the following cases:
- After profiling the data: Anomaly detection is automatically started following each profiling run.
- In monitoring projects, as part of the data quality (DQ) evaluation .
- Anomaly detection relies on one of the two models:
- Time-independent model: This model is used by default.
- Time-dependent model, based on the time series analysis.
- You can select time-independent or time-dependent anomaly detection to be used during profiling.
- The model is equipped to detect unexpected values of different kinds such as unexpected nulls, negatives, positives or zeros and changes from established trends.
- Time-dependent anomaly detection requires a minimum of 6 runs.