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foreign key match percent

foreign key match percent checks

Description
Column level check that ensures that there are no more than a minimum percentage of values matching values in another table column.

profile foreign key match percent

Check description
Verifies that the percentage of values in a column that matches values in another table column does not exceed the set count.

Check name Check type Time scale Sensor definition Quality rule
profile_foreign_key_match_percent profiling foreign_key_match_percent min_percent

Enable check (Shell)
To enable this check provide connection name and check name in check enable command 

dqo> check enable -c=connection_name -ch=profile_foreign_key_match_percent
Run check (Shell)
To run this check provide check name in check run command 
dqo> check run -ch=profile_foreign_key_match_percent
It is also possible to run this check on a specific connection. In order to do this, add the connection name to the below 
dqo> check run -c=connection_name -ch=profile_foreign_key_match_percent
It is additionally feasible to run this check on a specific table. In order to do this, add the table name to the below 
dqo> check run -c=connection_name -t=table_name -ch=profile_foreign_key_match_percent
It is furthermore viable to combine run this check on a specific column. In order to do this, add the column name to the below 
dqo> check run -c=connection_name -t=table_name -col=column_name -ch=profile_foreign_key_match_percent
Check structure (Yaml) 
      profiling_checks:
        integrity:
          profile_foreign_key_match_percent:
            parameters:
              foreign_table: dim_customer
              foreign_column: customer_id
            warning:
              min_percent: 100.0
            error:
              min_percent: 99.0
            fatal:
              min_percent: 95.0
Sample configuration (Yaml)
# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  columns:
    target_column:
      profiling_checks:
        integrity:
          profile_foreign_key_match_percent:
            parameters:
              foreign_table: dim_customer
              foreign_column: customer_id
            warning:
              min_percent: 100.0
            error:
              min_percent: 99.0
            fatal:
              min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested

BigQuery

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH) AS time_period,
    TIMESTAMP(DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

PostgreSQL

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Redshift

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Snowflake

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date)) AS time_period,
    TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

SQL Server

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0) AS time_period,
    CAST((DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]

Configuration with data grouping

Click to see more

Sample configuration (Yaml)

# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  default_grouping_name: group_by_country_and_state
  groupings:
    group_by_country_and_state:
      level_1:
        source: column_value
        column: country
      level_2:
        source: column_value
        column: state
  columns:
    target_column:
      profiling_checks:
        integrity:
          profile_foreign_key_match_percent:
            parameters:
              foreign_table: dim_customer
              foreign_column: customer_id
            warning:
              min_percent: 100.0
            error:
              min_percent: 99.0
            fatal:
              min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested
    country:
      labels:
      - column used as the first grouping key
    state:
      labels:
      - column used as the second grouping key
BigQuery 

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.`country` AS grouping_level_1,
    analyzed_table.`state` AS grouping_level_2,
    DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH) AS time_period,
    TIMESTAMP(DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

PostgreSQL 

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Redshift 

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Snowflake 

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date)) AS time_period,
    TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

SQL Server 

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.[country] AS grouping_level_1,
    analyzed_table.[state] AS grouping_level_2,
    DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0) AS time_period,
    CAST((DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]
GROUP BY analyzed_table.[country], analyzed_table.[state]
ORDER BY level_1, level_2
        ,

daily foreign key match percent

Check description
Verifies that the percentage of values in a column that matches values in another table column does not exceed the set count. Stores the most recent captured value for each day when the data quality check was evaluated.

Check name Check type Time scale Sensor definition Quality rule
daily_foreign_key_match_percent recurring daily foreign_key_match_percent min_percent

Enable check (Shell)
To enable this check provide connection name and check name in check enable command 

dqo> check enable -c=connection_name -ch=daily_foreign_key_match_percent
Run check (Shell)
To run this check provide check name in check run command 
dqo> check run -ch=daily_foreign_key_match_percent
It is also possible to run this check on a specific connection. In order to do this, add the connection name to the below 
dqo> check run -c=connection_name -ch=daily_foreign_key_match_percent
It is additionally feasible to run this check on a specific table. In order to do this, add the table name to the below 
dqo> check run -c=connection_name -t=table_name -ch=daily_foreign_key_match_percent
It is furthermore viable to combine run this check on a specific column. In order to do this, add the column name to the below 
dqo> check run -c=connection_name -t=table_name -col=column_name -ch=daily_foreign_key_match_percent
Check structure (Yaml) 
      recurring_checks:
        daily:
          integrity:
            daily_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
Sample configuration (Yaml)
# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  columns:
    target_column:
      recurring_checks:
        daily:
          integrity:
            daily_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested

BigQuery

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(CURRENT_TIMESTAMP() AS DATE) AS time_period,
    TIMESTAMP(CAST(CURRENT_TIMESTAMP() AS DATE)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

PostgreSQL

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(LOCALTIMESTAMP AS date) AS time_period,
    CAST((CAST(LOCALTIMESTAMP AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Redshift

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(LOCALTIMESTAMP AS date) AS time_period,
    CAST((CAST(LOCALTIMESTAMP AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Snowflake

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date) AS time_period,
    TO_TIMESTAMP(CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date)) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

SQL Server

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(SYSDATETIMEOFFSET() AS date) AS time_period,
    CAST((CAST(SYSDATETIMEOFFSET() AS date)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]

Configuration with data grouping

Click to see more

Sample configuration (Yaml)

# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  default_grouping_name: group_by_country_and_state
  groupings:
    group_by_country_and_state:
      level_1:
        source: column_value
        column: country
      level_2:
        source: column_value
        column: state
  columns:
    target_column:
      recurring_checks:
        daily:
          integrity:
            daily_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested
    country:
      labels:
      - column used as the first grouping key
    state:
      labels:
      - column used as the second grouping key
BigQuery 

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.`country` AS grouping_level_1,
    analyzed_table.`state` AS grouping_level_2,
    CAST(CURRENT_TIMESTAMP() AS DATE) AS time_period,
    TIMESTAMP(CAST(CURRENT_TIMESTAMP() AS DATE)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

PostgreSQL 

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    CAST(LOCALTIMESTAMP AS date) AS time_period,
    CAST((CAST(LOCALTIMESTAMP AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Redshift 

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    CAST(LOCALTIMESTAMP AS date) AS time_period,
    CAST((CAST(LOCALTIMESTAMP AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Snowflake 

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date) AS time_period,
    TO_TIMESTAMP(CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date)) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

SQL Server 

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.[country] AS grouping_level_1,
    analyzed_table.[state] AS grouping_level_2,
    CAST(SYSDATETIMEOFFSET() AS date) AS time_period,
    CAST((CAST(SYSDATETIMEOFFSET() AS date)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]
GROUP BY analyzed_table.[country], analyzed_table.[state]
ORDER BY level_1, level_2
        ,

monthly foreign key match percent

Check description
Verifies that the percentage of values in a column that matches values in another table column does not exceed the set count. Stores the most recent row count for each month when the data quality check was evaluated.

Check name Check type Time scale Sensor definition Quality rule
monthly_foreign_key_match_percent recurring monthly foreign_key_match_percent min_percent

Enable check (Shell)
To enable this check provide connection name and check name in check enable command 

dqo> check enable -c=connection_name -ch=monthly_foreign_key_match_percent
Run check (Shell)
To run this check provide check name in check run command 
dqo> check run -ch=monthly_foreign_key_match_percent
It is also possible to run this check on a specific connection. In order to do this, add the connection name to the below 
dqo> check run -c=connection_name -ch=monthly_foreign_key_match_percent
It is additionally feasible to run this check on a specific table. In order to do this, add the table name to the below 
dqo> check run -c=connection_name -t=table_name -ch=monthly_foreign_key_match_percent
It is furthermore viable to combine run this check on a specific column. In order to do this, add the column name to the below 
dqo> check run -c=connection_name -t=table_name -col=column_name -ch=monthly_foreign_key_match_percent
Check structure (Yaml) 
      recurring_checks:
        monthly:
          integrity:
            monthly_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
Sample configuration (Yaml)
# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  columns:
    target_column:
      recurring_checks:
        monthly:
          integrity:
            monthly_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested

BigQuery

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH) AS time_period,
    TIMESTAMP(DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

PostgreSQL

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Redshift

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Snowflake

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date)) AS time_period,
    TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

SQL Server

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0) AS time_period,
    CAST((DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]

Configuration with data grouping

Click to see more

Sample configuration (Yaml)

# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  default_grouping_name: group_by_country_and_state
  groupings:
    group_by_country_and_state:
      level_1:
        source: column_value
        column: country
      level_2:
        source: column_value
        column: state
  columns:
    target_column:
      recurring_checks:
        monthly:
          integrity:
            monthly_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested
    country:
      labels:
      - column used as the first grouping key
    state:
      labels:
      - column used as the second grouping key
BigQuery 

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.`country` AS grouping_level_1,
    analyzed_table.`state` AS grouping_level_2,
    DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH) AS time_period,
    TIMESTAMP(DATE_TRUNC(CAST(CURRENT_TIMESTAMP() AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

PostgreSQL 

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Redshift 

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(LOCALTIMESTAMP AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Snowflake 

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date)) AS time_period,
    TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(TO_TIMESTAMP_NTZ(LOCALTIMESTAMP()) AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

SQL Server 

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.[country] AS grouping_level_1,
    analyzed_table.[state] AS grouping_level_2,
    DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0) AS time_period,
    CAST((DATEADD(month, DATEDIFF(month, 0, SYSDATETIMEOFFSET()), 0)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]
GROUP BY analyzed_table.[country], analyzed_table.[state]
ORDER BY level_1, level_2
        ,

daily partition foreign key match percent

Check description
Verifies that the percentage of values in a column that matches values in another table column does not exceed the set count. Creates a separate data quality check (and an alert) for each daily partition.

Check name Check type Time scale Sensor definition Quality rule
daily_partition_foreign_key_match_percent partitioned daily foreign_key_match_percent min_percent

Enable check (Shell)
To enable this check provide connection name and check name in check enable command 

dqo> check enable -c=connection_name -ch=daily_partition_foreign_key_match_percent
Run check (Shell)
To run this check provide check name in check run command 
dqo> check run -ch=daily_partition_foreign_key_match_percent
It is also possible to run this check on a specific connection. In order to do this, add the connection name to the below 
dqo> check run -c=connection_name -ch=daily_partition_foreign_key_match_percent
It is additionally feasible to run this check on a specific table. In order to do this, add the table name to the below 
dqo> check run -c=connection_name -t=table_name -ch=daily_partition_foreign_key_match_percent
It is furthermore viable to combine run this check on a specific column. In order to do this, add the column name to the below 
dqo> check run -c=connection_name -t=table_name -col=column_name -ch=daily_partition_foreign_key_match_percent
Check structure (Yaml) 
      partitioned_checks:
        daily:
          integrity:
            daily_partition_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
Sample configuration (Yaml)
# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  columns:
    target_column:
      partitioned_checks:
        daily:
          integrity:
            daily_partition_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested

BigQuery

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(analyzed_table.`` AS DATE) AS time_period,
    TIMESTAMP(CAST(analyzed_table.`` AS DATE)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

PostgreSQL

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(analyzed_table."" AS date) AS time_period,
    CAST((CAST(analyzed_table."" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Redshift

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(analyzed_table."" AS date) AS time_period,
    CAST((CAST(analyzed_table."" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Snowflake

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(analyzed_table."" AS date) AS time_period,
    TO_TIMESTAMP(CAST(analyzed_table."" AS date)) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

SQL Server

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    CAST(analyzed_table.[] AS date) AS time_period,
    CAST((CAST(analyzed_table.[] AS date)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]
GROUP BY CAST(analyzed_table.[] AS date), CAST(analyzed_table.[] AS date)
ORDER BY CAST(analyzed_table.[] AS date)

Configuration with data grouping

Click to see more

Sample configuration (Yaml)

# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  default_grouping_name: group_by_country_and_state
  groupings:
    group_by_country_and_state:
      level_1:
        source: column_value
        column: country
      level_2:
        source: column_value
        column: state
  columns:
    target_column:
      partitioned_checks:
        daily:
          integrity:
            daily_partition_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested
    country:
      labels:
      - column used as the first grouping key
    state:
      labels:
      - column used as the second grouping key
BigQuery 

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.`country` AS grouping_level_1,
    analyzed_table.`state` AS grouping_level_2,
    CAST(analyzed_table.`` AS DATE) AS time_period,
    TIMESTAMP(CAST(analyzed_table.`` AS DATE)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

PostgreSQL 

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    CAST(analyzed_table."" AS date) AS time_period,
    CAST((CAST(analyzed_table."" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Redshift 

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    CAST(analyzed_table."" AS date) AS time_period,
    CAST((CAST(analyzed_table."" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Snowflake 

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    CAST(analyzed_table."" AS date) AS time_period,
    TO_TIMESTAMP(CAST(analyzed_table."" AS date)) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

SQL Server 

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.[country] AS grouping_level_1,
    analyzed_table.[state] AS grouping_level_2,
    CAST(analyzed_table.[] AS date) AS time_period,
    CAST((CAST(analyzed_table.[] AS date)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]
GROUP BY analyzed_table.[country], analyzed_table.[state], CAST(analyzed_table.[] AS date), CAST(analyzed_table.[] AS date)
ORDER BY level_1, level_2CAST(analyzed_table.[] AS date)

monthly partition foreign key match percent

Check description
Verifies that the percentage of values in a column that matches values in another table column does not exceed the set count. Creates a separate data quality check (and an alert) for each monthly partition.

Check name Check type Time scale Sensor definition Quality rule
monthly_partition_foreign_key_match_percent partitioned monthly foreign_key_match_percent min_percent

Enable check (Shell)
To enable this check provide connection name and check name in check enable command 

dqo> check enable -c=connection_name -ch=monthly_partition_foreign_key_match_percent
Run check (Shell)
To run this check provide check name in check run command 
dqo> check run -ch=monthly_partition_foreign_key_match_percent
It is also possible to run this check on a specific connection. In order to do this, add the connection name to the below 
dqo> check run -c=connection_name -ch=monthly_partition_foreign_key_match_percent
It is additionally feasible to run this check on a specific table. In order to do this, add the table name to the below 
dqo> check run -c=connection_name -t=table_name -ch=monthly_partition_foreign_key_match_percent
It is furthermore viable to combine run this check on a specific column. In order to do this, add the column name to the below 
dqo> check run -c=connection_name -t=table_name -col=column_name -ch=monthly_partition_foreign_key_match_percent
Check structure (Yaml) 
      partitioned_checks:
        monthly:
          integrity:
            monthly_partition_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
Sample configuration (Yaml)
# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  columns:
    target_column:
      partitioned_checks:
        monthly:
          integrity:
            monthly_partition_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested

BigQuery

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC(CAST(analyzed_table.`` AS DATE), MONTH) AS time_period,
    TIMESTAMP(DATE_TRUNC(CAST(analyzed_table.`` AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

PostgreSQL

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Redshift

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

Snowflake

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date)) AS time_period,
    TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc

SQL Server

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1) AS time_period,
    CAST((DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]
GROUP BY DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1), DATEADD(month, DATEDIFF(month, 0, analyzed_table.[]), 0)
ORDER BY DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1)

Configuration with data grouping

Click to see more

Sample configuration (Yaml)

# yaml-language-server: $schema=https://cloud.dqo.ai/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
  timestamp_columns:
    event_timestamp_column: col_event_timestamp
    ingestion_timestamp_column: col_inserted_at
  incremental_time_window:
    daily_partitioning_recent_days: 7
    monthly_partitioning_recent_months: 1
  default_grouping_name: group_by_country_and_state
  groupings:
    group_by_country_and_state:
      level_1:
        source: column_value
        column: country
      level_2:
        source: column_value
        column: state
  columns:
    target_column:
      partitioned_checks:
        monthly:
          integrity:
            monthly_partition_foreign_key_match_percent:
              parameters:
                foreign_table: dim_customer
                foreign_column: customer_id
              warning:
                min_percent: 100.0
              error:
                min_percent: 99.0
              fatal:
                min_percent: 95.0
      labels:
      - This is the column that is analyzed for data quality issues
    col_event_timestamp:
      labels:
      - optional column that stores the timestamp when the event/transaction happened
    col_inserted_at:
      labels:
      - optional column that stores the timestamp when row was ingested
    country:
      labels:
      - column used as the first grouping key
    state:
      labels:
      - column used as the second grouping key
BigQuery 

{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_project_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.`customer_id` IS NULL AND analyzed_table.`target_column` IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.`country` AS grouping_level_1,
    analyzed_table.`state` AS grouping_level_2,
    DATE_TRUNC(CAST(analyzed_table.`` AS DATE), MONTH) AS time_period,
    TIMESTAMP(DATE_TRUNC(CAST(analyzed_table.`` AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
LEFT OUTER JOIN `your-google-project-id`.`<target_schema>`.`dim_customer` AS foreign_table
ON analyzed_table.`target_column` = foreign_table.`customer_id`
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

PostgreSQL 

{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_postgresql_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Redshift 

{% import '/dialects/redshift.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date)) AS time_period,
    CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_redshift_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

Snowflake 

{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table."customer_id" IS NULL AND analyzed_table."target_column" IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table."country" AS grouping_level_1,
    analyzed_table."state" AS grouping_level_2,
    DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date)) AS time_period,
    TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table."" AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
LEFT OUTER JOIN "your_snowflake_database"."<target_schema>"."dim_customer" AS foreign_table
ON analyzed_table."target_column" = foreign_table."customer_id"
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc

SQL Server 

{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}

{%- macro render_foreign_table(foreign_table) -%}
{%- if foreign_table.find(".") < 0 -%}
   {{ lib.quote_identifier(lib.macro_database_name) }}.{{ lib.quote_identifier(lib.macro_schema_name) }}.{{- lib.quote_identifier(foreign_table) -}}
{%- else -%}
   {{ foreign_table }}
{%- endif -%}
{%- endmacro -%}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }} IS NULL AND {{ lib.render_target_column('analyzed_table')}} IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value
    {{- lib.render_data_grouping_projections('analyzed_table') }}
    {{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
LEFT OUTER JOIN {{ render_foreign_table(parameters.foreign_table) }} AS foreign_table
ON {{ lib.render_target_column('analyzed_table')}} = foreign_table.{{ lib.quote_identifier(parameters.foreign_column) }}
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}

SELECT
    100.0 * SUM(
        CASE
            WHEN foreign_table.[customer_id] IS NULL AND analyzed_table.[target_column] IS NOT NULL
                THEN 0
            ELSE 1
        END
    ) / COUNT(*) AS actual_value,
    analyzed_table.[country] AS grouping_level_1,
    analyzed_table.[state] AS grouping_level_2,
    DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1) AS time_period,
    CAST((DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
LEFT OUTER JOIN [your_sql_server_database].[<target_schema>].[dim_customer] AS foreign_table
ON analyzed_table.[target_column] = foreign_table.[customer_id]
GROUP BY analyzed_table.[country], analyzed_table.[state], DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1), DATEADD(month, DATEDIFF(month, 0, analyzed_table.[]), 0)
ORDER BY level_1, level_2DATEFROMPARTS(YEAR(CAST(analyzed_table.[] AS date)), MONTH(CAST(analyzed_table.[] AS date)), 1)