> ## Documentation Index > Fetch the complete documentation index at: https://docs.elementary-data.com/llms.txt > Use this file to discover all available pages before exploring further. # Anomaly Tests configuration params Let our Slack chatbot create the anomaly test you need. If your data set has a timestamp column that represents the creation time of a field, it is highly recommended configuring it as a `timestamp_column`. 
  
    All anomaly detection tests:
    \-- timestamp\_column: column name
    \-- where\_expression: sql expression
    \-- anomaly\_sensitivity: int
    \-- anomaly\_direction: \[both | spike | drop]
    \-- ignore\_small\_changes:
        spike\_failure\_percent\_threshold: int
        drop\_failure\_percent\_threshold: int
    \-- anomaly\_exclude\_metrics: \[SQL expression]

    Anomaly detection tests with timestamp\_column:
    \-- training\_period: int
        period: \[hour | day | week | month]
        count: int
    \-- detection\_period: int
        period: \[hour | day | week | month]
        count: int
    \-- exclude\_detection\_period\_from\_training: \[true | false]
    \-- time\_bucket:
        period: \[hour | day | week | month]
        count: int
    \-- seasonality: day\_of\_week
    \-- detection\_delay:
        period: \[hour | day | week | month]
        count: int

    dimension\_anomalies, column\_anomalies, all\_columns\_anomalies tests:
    \-- dimensions: sql expression

    volume\_anomalies test:
    \-- fail\_on\_zero: \[true | false]

    all\_columns\_anomalies test:
    \-- column\_anomalies: column monitors list
    \-- exclude\_prefix: string
    \-- exclude\_regexp: regex

    dimension\_anomalies test:
    \-- exclude\_final\_results: \[SQL where expression on fields value / average]

    event\_freshness\_anomalies:
    \-- event\_timestamp\_column: column name
    \-- update\_timestamp\_column: column name
## Example configurations ```yml Models theme={null} version: 2 models: - name: config: elementary: timestamp_column: < model timestamp column > data_tests: < here you will add elementary monitors as tests > - name: ## if no timestamp is configured, elementary will monitor without time filtering data_tests: ``` ```yml Models example theme={null} version: 2 models: - name: login_events config: elementary: timestamp_column: updated_at data_tests: - elementary.freshness_anomalies: config: tags: ["elementary"] - elementary.all_columns_anomalies: config: tags: ["elementary"] - name: users ## if no timestamp is configured, elementary will monitor without time filtering data_tests: - elementary.volume_anomalies: config: tags: ["elementary"] ``` ```yml Sources theme={null} version: 2 sources: - name: < some name > database: < database > schema: < schema > tables: - name: < table_name > config: elementary: timestamp_column: < source timestamp column > data_tests: ``` ```yml Sources example theme={null} version: 2 sources: - name: "my_non_dbt_table" database: "raw_events" schema: "product" tables: - name: "raw_product_login_events" config: elementary: timestamp_column: "loaded_at" data_tests: - elementary.volume_anomalies - elementary.all_columns_anomalies: arguments: column_anomalies: - null_count - missing_count - zero_count columns: - name: user_id data_tests: - elementary.column_anomalies ```