Skip to content

DBT: Anomaly Threshold Sensitivity

DBT model name: anomaly_threshold_sensitivity

Explore dependencies/lineage: link

Description

This is a view on metrics_anomaly_score that calculates if values of metrics from latest runs would have been considered anomalies in different anomaly scores. This can help you decide if there is a need to adjust the anomaly_score_threshold.

Details

Column Type Description

No data tests defined 🧐

Not referenced by any model or exposure.

Models

Macros

  • edr_condition_as_boolean
  • edr_quote_column

No called script or script source not found.

{{ config(materialized="view", bind=False) }}

with
    metrics_anomaly_score as (select * from {{ ref("metrics_anomaly_score") }}),

    score_sensitivity as (

        select
            full_table_name,
            column_name,
            metric_name,
            latest_metric_value,
            training_avg as metric_avg,
            training_stddev as metric_stddev,
            anomaly_score,
            {{ elementary.edr_condition_as_boolean("abs(anomaly_score) >= 1.5") }}
            as {{ elementary.edr_quote_column("is_anomaly_1_5") }},
            {{ elementary.edr_condition_as_boolean("abs(anomaly_score) >= 2") }}
            as {{ elementary.edr_quote_column("is_anomaly_2") }},
            {{ elementary.edr_condition_as_boolean("abs(anomaly_score) >= 2.5") }}
            as {{ elementary.edr_quote_column("is_anomaly_2_5") }},
            {{ elementary.edr_condition_as_boolean("abs(anomaly_score) >= 3") }}
            as {{ elementary.edr_quote_column("is_anomaly_3") }},
            {{ elementary.edr_condition_as_boolean("abs(anomaly_score) >= 3.5") }}
            as {{ elementary.edr_quote_column("is_anomaly_3_5") }},
            {{ elementary.edr_condition_as_boolean("abs(anomaly_score) >= 4") }}
            as {{ elementary.edr_quote_column("is_anomaly_4") }},
            {{ elementary.edr_condition_as_boolean("abs(anomaly_score) >= 4.5") }}
            as {{ elementary.edr_quote_column("is_anomaly_4_5") }}
        from metrics_anomaly_score
        where abs(anomaly_score) >= 1.5

    )

select *
from score_sensitivity