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Last updated: July 22, 2025

DQOps YAML file definitions

The definition of YAML files used by DQOps to configure the data sources, monitored tables, and the configuration of activated data quality checks.

ColumnProfilingCheckCategoriesSpec

Container of column level, preconfigured profiling checks.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
nulls Configuration of column level checks that detect null values. ColumnNullsProfilingChecksSpec
uniqueness Configuration of uniqueness checks on a column level. ColumnUniquenessProfilingChecksSpec
accepted_values Configuration of accepted values checks on a column level. ColumnAcceptedValuesProfilingChecksSpec
text Configuration of column level checks that verify text values. ColumnTextProfilingChecksSpec
whitespace Configuration of column level checks that detect blank and whitespace values. ColumnWhitespaceProfilingChecksSpec
conversions Configuration of conversion testing checks on a column level. ColumnConversionsProfilingChecksSpec
patterns Configuration of pattern match checks on a column level. ColumnPatternsProfilingChecksSpec
pii Configuration of Personal Identifiable Information (PII) checks on a column level. ColumnPiiProfilingChecksSpec
numeric Configuration of column level checks that verify numeric values. ColumnNumericProfilingChecksSpec
anomaly Configuration of anomaly checks on a column level that detect anomalies in numeric columns. ColumnAnomalyProfilingChecksSpec
datetime Configuration of datetime checks on a column level. ColumnDatetimeProfilingChecksSpec
bool Configuration of booleans checks on a column level. ColumnBoolProfilingChecksSpec
integrity Configuration of integrity checks on a column level. ColumnIntegrityProfilingChecksSpec
accuracy Configuration of accuracy checks on a column level. ColumnAccuracyProfilingChecksSpec
custom_sql Configuration of SQL checks that use custom SQL aggregated expressions and SQL conditions in data quality checks. ColumnCustomSqlProfilingChecksSpec
datatype Configuration of datatype checks on a column level. ColumnDatatypeProfilingChecksSpec
schema Configuration of schema checks on a column level. ColumnSchemaProfilingChecksSpec
comparisons Dictionary of configuration of checks for table comparisons at a column level. The key that identifies each comparison must match the name of a data comparison that is configured on the parent table. ColumnComparisonProfilingChecksSpecMap
custom Dictionary of custom checks. The keys are check names within this category. CustomCheckSpecMap

ColumnNullsProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for nulls.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_nulls_count Detects incomplete columns that contain any null values. Counts the number of rows having a null value. Raises a data quality issue when the count of null values is above a max_count threshold. ColumnNullsCountCheckSpec
profile_nulls_percent Detects incomplete columns that contain any null values. Measures the percentage of rows having a null value. Raises a data quality issue when the percentage of null values is above a max_percent threshold. ColumnNullsPercentCheckSpec
profile_nulls_percent_anomaly Detects day-to-day anomalies in the percentage of null values. Raises a data quality issue when the rate of null values increases or decreases too much during the last 90 days. ColumnNullPercentAnomalyStationaryCheckSpec
profile_not_nulls_count Verifies that a column contains a minimum number of non-null values. The default value of the min_count parameter is 1 to detect at least one value in a monitored column. Raises a data quality issue when the count of non-null values is below min_count. ColumnNotNullsCountCheckSpec
profile_not_nulls_percent Detects columns that contain too many non-null values. Measures the percentage of rows that have non-null values. Raises a data quality issue when the percentage of non-null values is above max_percentage. ColumnNotNullsPercentCheckSpec
profile_empty_column_found Detects empty columns that contain only null values. Counts the number of rows that have non-null values. Raises a data quality issue when the column is empty. ColumnEmptyColumnFoundCheckSpec
profile_nulls_percent_change Verifies that the null percent value in a column changed in a fixed rate since last readout. ColumnNullPercentChangeCheckSpec
profile_nulls_percent_change_1_day Verifies that the null percent value in a column changed in a fixed rate since last readout from yesterday. ColumnNullPercentChange1DayCheckSpec
profile_nulls_percent_change_7_days Verifies that the null percent value in a column changed in a fixed rate since last readout from last week. ColumnNullPercentChange7DaysCheckSpec
profile_nulls_percent_change_30_days Verifies that the null percent value in a column changed in a fixed rate since last readout from last month. ColumnNullPercentChange30DaysCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnUniquenessProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for negative values.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_distinct_count Verifies that the number of distinct values stays within an accepted range. ColumnDistinctCountCheckSpec
profile_distinct_percent Verifies that the percentage of distinct values in a column does not fall below the minimum accepted percent. ColumnDistinctPercentCheckSpec
profile_duplicate_count Verifies that the number of duplicate values in a column does not exceed the maximum accepted count. ColumnDuplicateCountCheckSpec
profile_duplicate_percent Verifies that the percentage of duplicate values in a column does not exceed the maximum accepted percentage. ColumnDuplicatePercentCheckSpec
profile_distinct_count_anomaly Verifies that the distinct count in a monitored column is within a two-tailed percentile from measurements made during the last 90 days. ColumnDistinctCountAnomalyDifferencingCheckSpec
profile_distinct_percent_anomaly Verifies that the distinct percent in a monitored column is within a two-tailed percentile from measurements made during the last 90 days. ColumnDistinctPercentAnomalyStationaryCheckSpec
profile_distinct_count_change Verifies that the distinct count in a monitored column has changed by a fixed rate since the last readout. ColumnDistinctCountChangeCheckSpec
profile_distinct_count_change_1_day Verifies that the distinct count in a monitored column has changed by a fixed rate since the last readout from yesterday. ColumnDistinctCountChange1DayCheckSpec
profile_distinct_count_change_7_days Verifies that the distinct count in a monitored column has changed by a fixed rate since the last readout from last week. ColumnDistinctCountChange7DaysCheckSpec
profile_distinct_count_change_30_days Verifies that the distinct count in a monitored column has changed by a fixed rate since the last readout from last month. ColumnDistinctCountChange30DaysCheckSpec
profile_distinct_percent_change Verifies that the distinct percent in a monitored column has changed by a fixed rate since the last readout. ColumnDistinctPercentChangeCheckSpec
profile_distinct_percent_change_1_day Verifies that the distinct percent in a monitored column has changed by a fixed rate since the last readout from yesterday. ColumnDistinctPercentChange1DayCheckSpec
profile_distinct_percent_change_7_days Verifies that the distinct percent in a monitored column has changed by a fixed rate since the last readout from last week. ColumnDistinctPercentChange7DaysCheckSpec
profile_distinct_percent_change_30_days Verifies that the distinct percent in a monitored column has changed by a fixed rate since the last readout from last month. ColumnDistinctPercentChange30DaysCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnAcceptedValuesProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for accepted values.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_text_found_in_set_percent The check measures the percentage of rows whose value in a tested column is one of values from a list of expected values or the column value is null. Verifies that the percentage of rows having a valid column value does not exceed the minimum accepted percentage. ColumnTextFoundInSetPercentCheckSpec
profile_number_found_in_set_percent The check measures the percentage of rows whose value in a tested column is one of values from a list of expected values or the column value is null. Verifies that the percentage of rows having a valid column value does not exceed the minimum accepted percentage. ColumnNumberFoundInSetPercentCheckSpec
profile_expected_text_values_in_use_count Verifies that the expected string values were found in the column. Raises a data quality issue when too many expected values were not found (were missing). ColumnExpectedTextValuesInUseCountCheckSpec
profile_expected_texts_in_top_values_count Verifies that the top X most popular column values contain all values from a list of expected values. ColumnExpectedTextsInTopValuesCountCheckSpec
profile_expected_numbers_in_use_count Verifies that the expected numeric values were found in the column. Raises a data quality issue when too many expected values were not found (were missing). ColumnExpectedNumbersInUseCountCheckSpec
profile_text_valid_country_code_percent Verifies that the percentage of valid country codes in a text column does not fall below the minimum accepted percentage ColumnTextValidCountryCodePercentCheckSpec
profile_text_valid_currency_code_percent Verifies that the percentage of valid currency codes in a text column does not fall below the minimum accepted percentage ColumnTextValidCurrencyCodePercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnTextProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking text values.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_text_min_length This check finds the length of the shortest text in a column. Then, it verifies that the minimum length is within an accepted range. It detects that the shortest text is too short. ColumnTextMinLengthCheckSpec
profile_text_max_length This check finds the length of the longest text in a column. Then, it verifies that the maximum length is within an accepted range. It detects that the texts are too long or not long enough. ColumnTextMaxLengthCheckSpec
profile_text_mean_length Verifies that the mean (average) length of texts in a column is within an accepted range. ColumnTextMeanLengthCheckSpec
profile_text_length_below_min_length The check counts the number of text values in the column that is below the length defined by the user as a parameter. ColumnTextLengthBelowMinLengthCheckSpec
profile_text_length_below_min_length_percent The check measures the percentage of text values in the column that is below the length defined by the user as a parameter. ColumnTextLengthBelowMinLengthPercentCheckSpec
profile_text_length_above_max_length The check counts the number of text values in the column that is above the length defined by the user as a parameter. ColumnTextLengthAboveMaxLengthCheckSpec
profile_text_length_above_max_length_percent The check measures the percentage of text values in the column that is above the length defined by the user as a parameter. ColumnTextLengthAboveMaxLengthPercentCheckSpec
profile_text_length_in_range_percent The check measures the percentage of those text values with length in the range provided by the user in the column. ColumnTextLengthInRangePercentCheckSpec
profile_min_word_count This check finds the lowest word count of text in a column. Then, it verifies that the minimum length is within an accepted range. It detects that the text contains too less words. ColumnTextMinWordCountCheckSpec
profile_max_word_count This check finds the highest word count of text in a column. Then, it verifies that the maximum length is within an accepted range. It detects that the text contains too many words. ColumnTextMaxWordCountCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnWhitespaceProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for whitespace and blank values in text columns.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_empty_text_found Detects empty texts (not null, zero-length texts). This check counts empty and raises a data quality issue when their count exceeds a max_count parameter value. ColumnWhitespaceEmptyTextFoundCheckSpec
profile_whitespace_text_found Detects texts that contain only spaces and other whitespace characters. It raises a data quality issue when their count exceeds a max_count parameter value. ColumnWhitespaceWhitespaceTextFoundCheckSpec
profile_null_placeholder_text_found Detects texts that are well-known placeholders of null values, such as None, null, n/a. It counts null placeholders and raises a data quality issue when their count exceeds a max_count parameter value. ColumnWhitespaceNullPlaceholderTextFoundCheckSpec
profile_empty_text_percent Detects empty texts (not null, zero-length texts) and measures their percentage in the column. This check verifies that the rate of empty strings in a column does not exceed the maximum accepted percentage. This check verifies that the rate of empty strings in a column does not exceed the maximum accepted percentage. ColumnWhitespaceEmptyTextPercentCheckSpec
profile_whitespace_text_percent Detects texts that contain only spaces and other whitespace characters and measures their percentage in the column. It raises a data quality issue when their rate exceeds a max_percent parameter value. ColumnWhitespaceWhitespaceTextPercentCheckSpec
profile_null_placeholder_text_percent Detects texts that are well-known placeholders of null values, such as None, null, n/a, and measures their percentage in the column. It raises a data quality issue when their rate exceeds a max_percent parameter value. ColumnWhitespaceNullPlaceholderTextPercentCheckSpec
profile_text_surrounded_by_whitespace_found Detects text values that are surrounded by whitespace characters on any side. This check counts whitespace-surrounded texts and raises a data quality issue when their count exceeds the max_count parameter value. ColumnWhitespaceTextSurroundedByWhitespaceFoundCheckSpec
profile_text_surrounded_by_whitespace_percent This check detects text values that are surrounded by whitespace characters on any side and measures their percentage. This check raises a data quality issue when their percentage exceeds the max_percent parameter value. ColumnWhitespaceTextSurroundedByWhitespacePercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnConversionsProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that verify if text values can be converted to a target data type.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_text_parsable_to_boolean_percent Verifies that the percentage of text values that are parsable to a boolean value does not fall below the minimum accepted percentage, text values identified as boolean placeholders are: 0, 1, true, false, t, f, yes, no, y, n. ColumnTextParsableToBooleanPercentCheckSpec
profile_text_parsable_to_integer_percent Verifies that the percentage text values that are parsable to an integer value in a column does not fall below the minimum accepted percentage ColumnTextParsableToIntegerPercentCheckSpec
profile_text_parsable_to_float_percent Verifies that the percentage text values that are parsable to a float value in a column does not fall below the minimum accepted percentage ColumnTextParsableToFloatPercentCheckSpec
profile_text_parsable_to_date_percent Verifies that the percentage text values that are parsable to a date value in a column does not fall below the minimum accepted percentage. DQOps uses a safe_cast when possible, otherwise the text is verified using a regular expression ColumnTextParsableToDatePercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnPatternsProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for values matching patterns (regular expressions) in text columns.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_text_not_matching_regex_found Verifies that the number of text values not matching the custom regular expression pattern does not exceed the maximum accepted count. ColumnTextNotMatchingRegexFoundCheckSpec
profile_texts_not_matching_regex_percent Verifies that the percentage of strings not matching the custom regular expression pattern does not exceed the maximum accepted percentage. ColumnTextsNotMatchingRegexPercentCheckSpec
profile_invalid_email_format_found Verifies that the number of invalid emails in a text column does not exceed the maximum accepted count. ColumnInvalidEmailFormatFoundCheckSpec
profile_invalid_email_format_percent Verifies that the percentage of invalid emails in a text column does not exceed the maximum accepted percentage. ColumnInvalidEmailFormatPercentCheckSpec
profile_text_not_matching_date_pattern_found Verifies that the number of texts not matching the date format regular expression does not exceed the maximum accepted count. ColumnTextNotMatchingDatePatternFoundCheckSpec
profile_text_not_matching_date_pattern_percent Verifies that the percentage of texts not matching the date format regular expression in a column does not exceed the maximum accepted percentage. ColumnTextNotMatchingDatePatternPercentCheckSpec
profile_text_not_matching_name_pattern_percent Verifies that the percentage of texts not matching the name regular expression does not exceed the maximum accepted percentage. ColumnTextNotMatchingNamePatternPercentCheckSpec
profile_invalid_uuid_format_found Verifies that the number of invalid UUIDs in a text column does not exceed the maximum accepted count. ColumnInvalidUuidFormatFoundCheckSpec
profile_invalid_uuid_format_percent Verifies that the percentage of invalid UUID in a text column does not exceed the maximum accepted percentage. ColumnInvalidUuidFormatPercentCheckSpec
profile_invalid_ip4_address_format_found Verifies that the number of invalid IP4 addresses in a text column does not exceed the maximum accepted count. ColumnInvalidIp4AddressFormatFoundCheckSpec
profile_invalid_ip6_address_format_found Verifies that the number of invalid IP6 addresses in a text column does not exceed the maximum accepted count. ColumnInvalidIp6AddressFormatFoundCheckSpec
profile_invalid_usa_phone_format_found Verifies that the number of invalid USA phone numbers in a text column does not exceed the maximum accepted count. ColumnInvalidUsaPhoneFoundCheckSpec
profile_invalid_usa_zipcode_format_found Verifies that the number of invalid zip codes in a text column does not exceed the maximum accepted count. ColumnInvalidUsaZipcodeFoundCheckSpec
profile_invalid_usa_phone_format_percent Verifies that the percentage of invalid USA phones number in a text column does not exceed the maximum accepted percentage. ColumnInvalidUsaPhonePercentCheckSpec
profile_invalid_usa_zipcode_format_percent Verifies that the percentage of invalid USA phones number in a text column does not exceed the maximum accepted percentage. ColumnInvalidUsaZipcodePercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnPiiProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for Personal Identifiable Information (PII).

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_contains_usa_phone_percent Detects USA phone numbers in text columns. Verifies that the percentage of rows that contains USA phone number in a column does not exceed the maximum accepted percentage. ColumnPiiContainsUsaPhonePercentCheckSpec
profile_contains_email_percent Detects emails in text columns. Verifies that the percentage of rows that contains valid emails in a column does not exceed the minimum accepted percentage. ColumnPiiContainsEmailPercentCheckSpec
profile_contains_usa_zipcode_percent Detects USA zip codes in text columns. Verifies that the percentage of rows that contains USA zip code in a column does not exceed the maximum accepted percentage. ColumnPiiContainsUsaZipcodePercentCheckSpec
profile_contains_ip4_percent Detects IP4 addresses in text columns. Verifies that the percentage of rows that contains valid IP4 address values in a column does not fall below the minimum accepted percentage. ColumnPiiContainsIp4PercentCheckSpec
profile_contains_ip6_percent Detects IP6 addresses in text columns. Verifies that the percentage of rows that contains valid IP6 address values in a column does not fall below the minimum accepted percentage. ColumnPiiContainsIp6PercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnNumericProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level for numeric values.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_number_below_min_value The check counts the number of values in the column that are below the value defined by the user as a parameter. ColumnNumberBelowMinValueCheckSpec
profile_number_above_max_value The check counts the number of values in the column that are above the value defined by the user as a parameter. ColumnNumberAboveMaxValueCheckSpec
profile_negative_values Verifies that the number of negative values in a column does not exceed the maximum accepted count. ColumnNegativeCountCheckSpec
profile_negative_values_percent Verifies that the percentage of negative values in a column does not exceed the maximum accepted percentage. ColumnNegativePercentCheckSpec
profile_number_below_min_value_percent The check counts the percentage of values in the column that are below the value defined by the user as a parameter. ColumnNumberBelowMinValuePercentCheckSpec
profile_number_above_max_value_percent The check counts the percentage of values in the column that are above the value defined by the user as a parameter. ColumnNumberAboveMaxValuePercentCheckSpec
profile_number_in_range_percent Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. ColumnNumberInRangePercentCheckSpec
profile_integer_in_range_percent Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. ColumnIntegerInRangePercentCheckSpec
profile_min_in_range Verifies that the minimum value in a column is not outside the expected range. ColumnMinInRangeCheckSpec
profile_max_in_range Verifies that the maximum value in a column is not outside the expected range. ColumnMaxInRangeCheckSpec
profile_sum_in_range Verifies that the sum of all values in a column is not outside the expected range. ColumnSumInRangeCheckSpec
profile_mean_in_range Verifies that the average (mean) of all values in a column is not outside the expected range. ColumnMeanInRangeCheckSpec
profile_median_in_range Verifies that the median of all values in a column is not outside the expected range. ColumnMedianInRangeCheckSpec
profile_percentile_in_range Verifies that the percentile of all values in a column is not outside the expected range. ColumnPercentileInRangeCheckSpec
profile_percentile_10_in_range Verifies that the percentile 10 of all values in a column is not outside the expected range. ColumnPercentile10InRangeCheckSpec
profile_percentile_25_in_range Verifies that the percentile 25 of all values in a column is not outside the expected range. ColumnPercentile25InRangeCheckSpec
profile_percentile_75_in_range Verifies that the percentile 75 of all values in a column is not outside the expected range. ColumnPercentile75InRangeCheckSpec
profile_percentile_90_in_range Verifies that the percentile 90 of all values in a column is not outside the expected range. ColumnPercentile90InRangeCheckSpec
profile_sample_stddev_in_range Verifies that the sample standard deviation of all values in a column is not outside the expected range. ColumnSampleStddevInRangeCheckSpec
profile_population_stddev_in_range Verifies that the population standard deviation of all values in a column is not outside the expected range. ColumnPopulationStddevInRangeCheckSpec
profile_sample_variance_in_range Verifies that the sample variance of all values in a column is not outside the expected range. ColumnSampleVarianceInRangeCheckSpec
profile_population_variance_in_range Verifies that the population variance of all values in a column is not outside the expected range. ColumnPopulationVarianceInRangeCheckSpec
profile_invalid_latitude Verifies that the number of invalid latitude values in a column does not exceed the maximum accepted count. ColumnInvalidLatitudeCountCheckSpec
profile_valid_latitude_percent Verifies that the percentage of valid latitude values in a column does not fall below the minimum accepted percentage. ColumnValidLatitudePercentCheckSpec
profile_invalid_longitude Verifies that the number of invalid longitude values in a column does not exceed the maximum accepted count. ColumnInvalidLongitudeCountCheckSpec
profile_valid_longitude_percent Verifies that the percentage of valid longitude values in a column does not fall below the minimum accepted percentage. ColumnValidLongitudePercentCheckSpec
profile_non_negative_values Verifies that the number of non-negative values in a column does not exceed the maximum accepted count. ColumnNonNegativeCountCheckSpec
profile_non_negative_values_percent Verifies that the percentage of non-negative values in a column does not exceed the maximum accepted percentage. ColumnNonNegativePercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnAnomalyProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level for detecting anomalies.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_sum_anomaly Verifies that the sum in a column changes in a rate within a percentile boundary during the last 90 days. ColumnSumAnomalyDifferencingCheckSpec
profile_mean_anomaly Verifies that the mean value in a column changes in a rate within a percentile boundary during the last 90 days. ColumnMeanAnomalyStationaryCheckSpec
profile_median_anomaly Verifies that the median in a column changes in a rate within a percentile boundary during the last 90 days. ColumnMedianAnomalyStationaryCheckSpec
profile_min_anomaly Detects new outliers, which are new minimum values, much below the last known minimum value. If the minimum value is constantly changing, detects outliers as the biggest change of the minimum value during the last 90 days. ColumnMinAnomalyDifferencingCheckSpec
profile_max_anomaly Detects new outliers, which are new maximum values, much above the last known maximum value. If the maximum value is constantly changing, detects outliers as the biggest change of the maximum value during the last 90 days. ColumnMaxAnomalyDifferencingCheckSpec
profile_mean_change Verifies that the mean value in a column changed in a fixed rate since the last readout. ColumnMeanChangeCheckSpec
profile_mean_change_1_day Verifies that the mean value in a column changed in a fixed rate since the last readout from yesterday. ColumnMeanChange1DayCheckSpec
profile_mean_change_7_days Verifies that the mean value in a column changed in a fixed rate since the last readout from the last week. ColumnMeanChange7DaysCheckSpec
profile_mean_change_30_days Verifies that the mean value in a column changed in a fixed rate since the last readout from the last month. ColumnMeanChange30DaysCheckSpec
profile_median_change Verifies that the median in a column changed in a fixed rate since the last readout. ColumnMedianChangeCheckSpec
profile_median_change_1_day Verifies that the median in a column changed in a fixed rate since the last readout from yesterday. ColumnMedianChange1DayCheckSpec
profile_median_change_7_days Verifies that the median in a column changed in a fixed rate since the last readout from the last week. ColumnMedianChange7DaysCheckSpec
profile_median_change_30_days Verifies that the median in a column changed in a fixed rate since the last readout from the last month. ColumnMedianChange30DaysCheckSpec
profile_sum_change Verifies that the sum in a column changed in a fixed rate since the last readout. ColumnSumChangeCheckSpec
profile_sum_change_1_day Verifies that the sum in a column changed in a fixed rate since the last readout from yesterday. ColumnSumChange1DayCheckSpec
profile_sum_change_7_days Verifies that the sum in a column changed in a fixed rate since the last readout from last week. ColumnSumChange7DaysCheckSpec
profile_sum_change_30_days Verifies that the sum in a column changed in a fixed rate since the last readout from last month. ColumnSumChange30DaysCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnDatetimeProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for datetime.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_date_values_in_future_percent Detects dates in the future in date, datetime and timestamp columns. Measures a percentage of dates in the future. Raises a data quality issue when too many future dates are found. ColumnDateValuesInFuturePercentCheckSpec
profile_date_in_range_percent Verifies that the dates in date, datetime, or timestamp columns are within a reasonable range of dates. The default configuration detects fake dates such as 1900-01-01 and 2099-12-31. Measures the percentage of valid dates and raises a data quality issue when too many dates are found. ColumnDateInRangePercentCheckSpec
profile_text_match_date_format_percent Verifies that the values in text columns match one of the predefined date formats, such as an ISO 8601 date. Measures the percentage of valid date strings and raises a data quality issue when too many invalid date strings are found. ColumnTextMatchDateFormatPercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnBoolProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for booleans.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_true_percent Measures the percentage of true values in a boolean column and verifies that it is within the accepted range. ColumnTruePercentCheckSpec
profile_false_percent Measures the percentage of false values in a boolean column and verifies that it is within the accepted range. ColumnFalsePercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnIntegrityProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for integrity.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_lookup_key_not_found Detects invalid values that are not present in a dictionary table using an outer join query. Counts the number of invalid keys. ColumnIntegrityLookupKeyNotFoundCountCheckSpec
profile_lookup_key_found_percent Measures the percentage of valid values that are present in a dictionary table. Joins this table to a dictionary table using an outer join. ColumnIntegrityForeignKeyMatchPercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnAccuracyProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for accuracy.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_total_sum_match_percent Verifies that percentage of the difference in total sum of a column in a table and total sum of a column of another table does not exceed the set number. ColumnAccuracyTotalSumMatchPercentCheckSpec
profile_total_min_match_percent Verifies that the percentage of difference in total min of a column in a table and total min of a column of another table does not exceed the set number. ColumnAccuracyTotalMinMatchPercentCheckSpec
profile_total_max_match_percent Verifies that the percentage of difference in total max of a column in a table and total max of a column of another table does not exceed the set number. ColumnAccuracyTotalMaxMatchPercentCheckSpec
profile_total_average_match_percent Verifies that the percentage of difference in total average of a column in a table and total average of a column of another table does not exceed the set number. ColumnAccuracyTotalAverageMatchPercentCheckSpec
profile_total_not_null_count_match_percent Verifies that the percentage of difference in total not null count of a column in a table and total not null count of a column of another table does not exceed the set number. Stores the most recent captured value for each day when the data quality check was evaluated. ColumnAccuracyTotalNotNullCountMatchPercentCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnCustomSqlProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are using custom SQL expressions (conditions).

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_sql_condition_failed_on_column Verifies that a custom SQL expression is met for each row. Counts the number of rows where the expression is not satisfied, and raises an issue if too many failures were detected. This check is used also to compare values between the current column and another column: `{alias}.{column} > col_tax`. ColumnSqlConditionFailedCheckSpec
profile_sql_condition_passed_percent_on_column Verifies that a minimum percentage of rows passed a custom SQL condition (expression). Reference the current column by using tokens, for example: `{alias}.{column} > {alias}.col_tax`. ColumnSqlConditionPassedPercentCheckSpec
profile_sql_aggregate_expression_on_column Verifies that a custom aggregated SQL expression (MIN, MAX, etc.) is not outside the expected range. ColumnSqlAggregateExpressionCheckSpec
profile_sql_invalid_value_count_on_column Runs a custom query that retrieves invalid values found in a column and returns the number of them, and raises an issue if too many failures were detected. This check is used for setting testing queries or ready queries used by users in their own systems (legacy SQL queries). For example, when this check is applied on a column. The condition can find invalid values in the column which have values lower than 18 using an SQL query: `SELECT {column} FROM {table} WHERE {column} < 18`. ColumnSqlInvalidValueCountCheckSpec
profile_import_custom_result_on_column Runs a custom query that retrieves a result of a data quality check performed in the data engineering, whose result (the severity level) is pulled from a separate table. ColumnSqlImportCustomResultCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnDatatypeProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking for datatype.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_detected_datatype_in_text Detects the data type of text values stored in the column. The sensor returns the code of the detected type of column data: 1 - integers, 2 - floats, 3 - dates, 4 - datetimes, 5 - timestamps, 6 - booleans, 7 - strings, 8 - mixed data types. Raises a data quality issue when the detected data type does not match the expected data type. ColumnDetectedDatatypeInTextCheckSpec
profile_detected_datatype_in_text_changed Detects that the data type of texts stored in a text column has changed since the last verification. The sensor returns the detected data type of a column: 1 - integers, 2 - floats, 3 - dates, 4 - datetimes, 5 - timestamps, 6 - booleans, 7 - strings, 8 - mixed data types. ColumnDatatypeDetectedDatatypeInTextChangedCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnSchemaProfilingChecksSpec

Container of built-in preconfigured data quality checks on a column level that are checking the column schema.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_column_exists Checks the metadata of the monitored table and verifies if the column exists. ColumnSchemaColumnExistsCheckSpec
profile_column_type_changed Checks the metadata of the monitored column and detects if the data type (including the length, precision, scale, nullability) has changed. ColumnSchemaTypeChangedCheckSpec
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap

ColumnComparisonProfilingChecksSpecMap

Container of comparison checks for each defined data comparison. The name of the key in this dictionary must match a name of a table comparison that is defined on the parent table. Contains configuration of column level comparison checks. Each column level check container also defines the name of the reference column name to which we are comparing.

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
self Dict[string, ColumnComparisonProfilingChecksSpec]

ColumnComparisonProfilingChecksSpec

Container of built-in preconfigured column level comparison checks that compare min/max/sum/mean/nulls measures between the column in the tested (parent) table and a matching reference column in the reference table (the source of truth).

The structure of this object is described below

 Property name   Description                       Data type   Enum values   Default value   Sample values 
profile_sum_match Verifies that percentage of the difference between the sum of values in a tested column in a parent table and the sum of a values in a column in the reference table. The difference must be below defined percentage thresholds. ColumnComparisonSumMatchCheckSpec
profile_min_match Verifies that percentage of the difference between the minimum value in a tested column in a parent table and the minimum value in a column in the reference table. The difference must be below defined percentage thresholds. ColumnComparisonMinMatchCheckSpec
profile_max_match Verifies that percentage of the difference between the maximum value in a tested column in a parent table and the maximum value in a column in the reference table. The difference must be below defined percentage thresholds. ColumnComparisonMaxMatchCheckSpec
profile_mean_match Verifies that percentage of the difference between the mean (average) value in a tested column in a parent table and the mean (average) value in a column in the reference table. The difference must be below defined percentage thresholds. ColumnComparisonMeanMatchCheckSpec
profile_not_null_count_match Verifies that percentage of the difference between the count of not null values in a tested column in a parent table and the count of not null values in a column in the reference table. The difference must be below defined percentage thresholds. ColumnComparisonNotNullCountMatchCheckSpec
profile_null_count_match Verifies that percentage of the difference between the count of null values in a tested column in a parent table and the count of null values in a column in the reference table. The difference must be below defined percentage thresholds. ColumnComparisonNullCountMatchCheckSpec
profile_distinct_count_match Verifies that percentage of the difference between the count of distinct values in a tested column in a parent table and the count of distinct values in a column in the reference table. The difference must be below defined percentage thresholds. ColumnComparisonDistinctCountMatchCheckSpec
reference_column The name of the reference column name in the reference table. It is the column to which the current column is compared to. string
custom_checks Dictionary of additional custom checks within this category. The keys are check names defined in the definition section. The sensor parameters and rules should match the type of the configured sensor and rule for the custom check. CustomCategoryCheckSpecMap