Last updated: July 22, 2025

List of column level numeric data quality checks

This is a list of numeric column data quality checks supported by DQOps and a brief description of what data quality issued they detect.

column-level numeric checks

Validates that the data in a numeric column is in the expected format or within predefined ranges.

number below min value

This check finds numeric values smaller than the minimum accepted value. It counts the values that are too small. This check raises a data quality issue when the count of too small values exceeds the maximum accepted count.

Data quality check name	Friendly name	Check type	Description
`profile_number_below_min_value`	Find invalid numeric values below an expected minimum value	profiling	The check counts the number of values in the column that are below the value defined by the user as a parameter.
`daily_number_below_min_value`	Find invalid numeric values below an expected minimum value	monitoring	The check counts the number of values in the column that are below the value defined by the user as a parameter. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_number_below_min_value`	Find invalid numeric values below an expected minimum value	monitoring	The check counts the number of values in the column that are below the value defined by the user as a parameter. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_number_below_min_value`	Find invalid numeric values below an expected minimum value	partitioned	The check counts the number of values in the column that are below the value defined by the user as a parameter. Stores a separate data quality check result for each daily partition.
`monthly_partition_number_below_min_value`	Find invalid numeric values below an expected minimum value	partitioned	The check counts the number of values in the column that are below the value defined by the user as a parameter. Stores a separate data quality check result for each monthly partition.

number above max value

This check finds numeric values bigger than the maximum accepted value. It counts the values that are too big. This check raises a data quality issue when the count of too big values exceeds the maximum accepted count.

Data quality check name	Friendly name	Check type	Description
`profile_number_above_max_value`	Find invalid numeric values above an expected maximum value	profiling	The check counts the number of values in the column that are above the value defined by the user as a parameter.
`daily_number_above_max_value`	Find invalid numeric values above an expected maximum value	monitoring	The check counts the number of values in the column that are above the value defined by the user as a parameter. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_number_above_max_value`	Find invalid numeric values above an expected maximum value	monitoring	The check counts the number of values in the column that are above the value defined by the user as a parameter. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_number_above_max_value`	Find invalid numeric values above an expected maximum value	partitioned	The check counts the number of values in the column that are above the value defined by the user as a parameter. Stores a separate data quality check result for each daily partition.
`monthly_partition_number_above_max_value`	Find invalid numeric values above an expected maximum value	partitioned	The check counts the number of values in the column that are above the value defined by the user as a parameter. Stores a separate data quality check result for each monthly partition.

negative values

This check finds and counts negative values in a numeric column. It raises a data quality issue when the count of negative values is above the maximum accepted count.

Data quality check name	Friendly name	Check type	Description
`profile_negative_values`	Maximum count of negative values	profiling	Verifies that the number of negative values in a column does not exceed the maximum accepted count.
`daily_negative_values`	Maximum count of negative values	monitoring	Verifies that the number of negative values in a column does not exceed the maximum accepted count. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_negative_values`	Maximum count of negative values	monitoring	Verifies that the number of negative values in a column does not exceed the maximum accepted count. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_negative_values`	Maximum count of negative values	partitioned	Verifies that the number of negative values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each daily partition.
`monthly_partition_negative_values`	Maximum count of negative values	partitioned	Verifies that the number of negative values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each monthly partition.

negative values percent

This check finds negative values in a numeric column. It measures the percentage of negative values and raises a data quality issue when the rate of negative values exceeds the maximum accepted percentage.

Data quality check name	Friendly name	Check type	Description
`profile_negative_values_percent`	Maximum percentage of negative values	profiling	Verifies that the percentage of negative values in a column does not exceed the maximum accepted percentage.
`daily_negative_values_percent`	Maximum percentage of negative values	monitoring	Verifies that the percentage of negative values in a column does not exceed the maximum accepted percentage. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_negative_values_percent`	Maximum percentage of negative values	monitoring	Verifies that the percentage of negative values in a column does not exceed the maximum accepted percentage. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_negative_values_percent`	Maximum percentage of negative values	partitioned	Verifies that the percentage of negative values in a column does not exceed the maximum accepted percentage. Stores a separate data quality check result for each daily partition.
`monthly_partition_negative_values_percent`	Maximum percentage of negative values	partitioned	Verifies that the percentage of negative values in a column does not exceed the maximum accepted percentage. Stores a separate data quality check result for each monthly partition.

number below min value percent

This check finds numeric values smaller than the minimum accepted value. It measures the percentage of values that are too small. This check raises a data quality issue when the percentage of values that are too small exceeds the maximum accepted percentage.

Data quality check name	Friendly name	Check type	Description
`profile_number_below_min_value_percent`	Maximum percentage of numeric values below the minimum value	profiling	The check counts the percentage of values in the column that are below the value defined by the user as a parameter.
`daily_number_below_min_value_percent`	Maximum percentage of numeric values below the minimum value	monitoring	The check counts the percentage of values in the column that are below the value defined by the user as a parameter. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_number_below_min_value_percent`	Maximum percentage of numeric values below the minimum value	monitoring	The check counts the percentage of values in the column that are below the value defined by the user as a parameter. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_number_below_min_value_percent`	Maximum percentage of numeric values below the minimum value	partitioned	The check counts the percentage of values in the column that are below the value defined by the user as a parameter. Stores a separate data quality check result for each daily partition.
`monthly_partition_number_below_min_value_percent`	Maximum percentage of numeric values below the minimum value	partitioned	The check counts the percentage of values in the column that are below the value defined by the user as a parameter. Stores a separate data quality check result for each monthly partition.

number above max value percent

This check finds numeric values bigger than the maximum accepted value. It measures the percentage of values that are too big. This check raises a data quality issue when the percentage of values that are too big exceeds the maximum accepted percentage.

Data quality check name	Friendly name	Check type	Description
`profile_number_above_max_value_percent`	Maximum percentage of numeric values above the maximum value	profiling	The check counts the percentage of values in the column that are above the value defined by the user as a parameter.
`daily_number_above_max_value_percent`	Maximum percentage of numeric values above the maximum value	monitoring	The check counts the percentage of values in the column that are above the value defined by the user as a parameter. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_number_above_max_value_percent`	Maximum percentage of numeric values above the maximum value	monitoring	The check counts the percentage of values in the column that are above the value defined by the user as a parameter. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_number_above_max_value_percent`	Maximum percentage of numeric values above the maximum value	partitioned	The check counts the percentage of values in the column that are above the value defined by the user as a parameter. Stores a separate data quality check result for each daily partition.
`monthly_partition_number_above_max_value_percent`	Maximum percentage of numeric values above the maximum value	partitioned	The check counts the percentage of values in the column that are above the value defined by the user as a parameter. Stores a separate data quality check result for each monthly partition.

number in range percent

This check verifies that values in a numeric column are within an accepted range. It measures the percentage of values within the valid range and raises a data quality issue when the rate of valid values is below a minimum accepted percentage.

Data quality check name	Friendly name	Check type	Description
`profile_number_in_range_percent`	Maximum percentage of rows containing numeric values in the range	profiling	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage.
`daily_number_in_range_percent`	Maximum percentage of rows containing numeric values in the range	monitoring	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_number_in_range_percent`	Maximum percentage of rows containing numeric values in the range	monitoring	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_number_in_range_percent`	Maximum percentage of rows containing numeric values in the range	partitioned	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores a separate data quality check result for each daily partition.
`monthly_partition_number_in_range_percent`	Maximum percentage of rows containing numeric values in the range	partitioned	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores a separate data quality check result for each monthly partition.

integer in range percent

This check verifies that numeric values are within a range of accepted values. It measures the percentage of values in the range and raises a data quality issue when the percentage of valid values is below an accepted rate.

Data quality check name	Friendly name	Check type	Description
`profile_integer_in_range_percent`	Maximum percentage of rows containing integer values in the range	profiling	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage.
`daily_integer_in_range_percent`	Maximum percentage of rows containing integer values in the range	monitoring	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_integer_in_range_percent`	Maximum percentage of rows containing integer values in the range	monitoring	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_integer_in_range_percent`	Maximum percentage of rows containing integer values in the range	partitioned	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores a separate data quality check result for each daily partition.
`monthly_partition_integer_in_range_percent`	Maximum percentage of rows containing integer values in the range	partitioned	Verifies that the percentage of values from range in a column does not exceed the minimum accepted percentage. Stores a separate data quality check result for each monthly partition.

min in range

This check finds a minimum value in a numeric column. It verifies that the minimum value is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_min_in_range`	Minimum numeric value is in the range	profiling	Verifies that the minimum value in a column is not outside the expected range.
`daily_min_in_range`	Minimum numeric value is in the range	monitoring	Verifies that the minimum value in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_min_in_range`	Minimum numeric value is in the range	monitoring	Verifies that the minimum value in a column does not exceed the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_min_in_range`	Minimum numeric value is in the range	partitioned	Verifies that the minimum value in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_min_in_range`	Minimum numeric value is in the range	partitioned	Verifies that the minimum value in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

max in range

This check finds a maximum value in a numeric column. It verifies that the maximum value is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_max_in_range`	Maximum numeric value is in the range	profiling	Verifies that the maximum value in a column is not outside the expected range.
`daily_max_in_range`	Maximum numeric value is in the range	monitoring	Verifies that the maximum value in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_max_in_range`	Maximum numeric value is in the range	monitoring	Verifies that the maximum value in a column does not exceed the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_max_in_range`	Maximum numeric value is in the range	partitioned	Verifies that the maximum value in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_max_in_range`	Maximum numeric value is in the range	partitioned	Verifies that the maximum value in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

sum in range

This check calculates a sum of numeric values. It verifies that the sum is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_sum_in_range`	Sum of numeric values is in the range	profiling	Verifies that the sum of all values in a column is not outside the expected range.
`daily_sum_in_range`	Sum of numeric values is in the range	monitoring	Verifies that the sum of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_sum_in_range`	Sum of numeric values is in the range	monitoring	Verifies that the sum of all values in a column does not exceed the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_sum_in_range`	Sum of numeric values is in the range	partitioned	Verifies that the sum of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_sum_in_range`	Sum of numeric values is in the range	partitioned	Verifies that the sum of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

mean in range

This check calculates a mean (average) value in a numeric column. It verifies that the average value is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_mean_in_range`	Mean (average) of numeric values is in the range	profiling	Verifies that the average (mean) of all values in a column is not outside the expected range.
`daily_mean_in_range`	Mean (average) of numeric values is in the range	monitoring	Verifies that the average (mean) of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_mean_in_range`	Mean (average) of numeric values is in the range	monitoring	Verifies that the average (mean) of all values in a column does not exceed the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_mean_in_range`	Mean (average) of numeric values is in the range	partitioned	Verifies that the average (mean) of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_mean_in_range`	Mean (average) of numeric values is in the range	partitioned	Verifies that the average (mean) of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

median in range

This check finds a median value in a numeric column. It verifies that the median value is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_median_in_range`	Median of numeric values is in the range	profiling	Verifies that the median of all values in a column is not outside the expected range.
`daily_median_in_range`	Median of numeric values is in the range	monitoring	Verifies that the median of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`monthly_median_in_range`	Median of numeric values is in the range	monitoring	Verifies that the median of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_median_in_range`	Median of numeric values is in the range	partitioned	Verifies that the median of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_median_in_range`	Median of numeric values is in the range	partitioned	Verifies that the median of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

percentile in range

This check finds a requested percentile value of numeric values. The percentile is configured as a value in the range [0, 1]. This check verifies that the given percentile is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_percentile_in_range`	The selected percentile of numeric values is in the range	profiling	Verifies that the percentile of all values in a column is not outside the expected range.
`daily_percentile_in_range`	The selected percentile of numeric values is in the range	monitoring	Verifies that the percentile of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_percentile_in_range`	The selected percentile of numeric values is in the range	monitoring	Verifies that the percentile of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_percentile_in_range`	The selected percentile of numeric values is in the range	partitioned	Verifies that the percentile of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_percentile_in_range`	The selected percentile of numeric values is in the range	partitioned	Verifies that the percentile of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

percentile 10 in range

This check finds the 10th percentile value in a numeric column. The 10th percentile is a value greater than 10% of the smallest values and smaller than the remaining 90% of other values. This check verifies that the 10th percentile is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_percentile_10_in_range`	The selected 10th percentile of numeric values is in the range	profiling	Verifies that the percentile 10 of all values in a column is not outside the expected range.
`daily_percentile_10_in_range`	The selected 10th percentile of numeric values is in the range	monitoring	Verifies that the percentile 10 of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_percentile_10_in_range`	The selected 10th percentile of numeric values is in the range	monitoring	Verifies that the percentile 10 of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_percentile_10_in_range`	The selected 10th percentile of numeric values is in the range	partitioned	Verifies that the percentile 10 of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_percentile_10_in_range`	The selected 10th percentile of numeric values is in the range	partitioned	Verifies that the percentile 10 of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

percentile 25 in range

This check finds the 25th percentile value in a numeric column. The 10th percentile is a value greater than 25% of the smallest values and smaller than the remaining 75% of other values. This check verifies that the 25th percentile is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_percentile_25_in_range`	The selected 25th percentile of numeric values is in the range	profiling	Verifies that the percentile 25 of all values in a column is not outside the expected range.
`daily_percentile_25_in_range`	The selected 25th percentile of numeric values is in the range	monitoring	Verifies that the percentile 25 of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_percentile_25_in_range`	The selected 25th percentile of numeric values is in the range	monitoring	Verifies that the percentile 25 of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_percentile_25_in_range`	The selected 25th percentile of numeric values is in the range	partitioned	Verifies that the percentile 25 of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_percentile_25_in_range`	The selected 25th percentile of numeric values is in the range	partitioned	Verifies that the percentile 25 of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

percentile 75 in range

This check finds the 75th percentile value in a numeric column. The 75th percentile is a value greater than 75% of the smallest values and smaller than the remaining 25% of other values. This check verifies that the 75th percentile is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_percentile_75_in_range`	The selected 75th percentile of numeric values is in the range	profiling	Verifies that the percentile 75 of all values in a column is not outside the expected range.
`daily_percentile_75_in_range`	The selected 75th percentile of numeric values is in the range	monitoring	Verifies that the percentile 75 of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_percentile_75_in_range`	The selected 75th percentile of numeric values is in the range	monitoring	Verifies that the percentile 75 of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_percentile_75_in_range`	The selected 75th percentile of numeric values is in the range	partitioned	Verifies that the percentile 75 of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_percentile_75_in_range`	The selected 75th percentile of numeric values is in the range	partitioned	Verifies that the percentile 75 of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

percentile 90 in range

This check finds the 90th percentile value in a numeric column. The 90th percentile is a value greater than 90% of the smallest values and smaller than the remaining 10% of other values. This check verifies that the 90th percentile is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_percentile_90_in_range`	The selected 90th percentile of numeric values is in the range	profiling	Verifies that the percentile 90 of all values in a column is not outside the expected range.
`daily_percentile_90_in_range`	The selected 90th percentile of numeric values is in the range	monitoring	Verifies that the percentile 90 of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_percentile_90_in_range`	The selected 90th percentile of numeric values is in the range	monitoring	Verifies that the percentile 90 of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_percentile_90_in_range`	The selected 90th percentile of numeric values is in the range	partitioned	Verifies that the percentile 90 of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_percentile_90_in_range`	The selected 90th percentile of numeric values is in the range	partitioned	Verifies that the percentile 90 of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

sample stddev in range

This check calculates the standard deviation of numeric values. It verifies that the standard deviation is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_sample_stddev_in_range`	Standard deviation of numeric values is in the range	profiling	Verifies that the sample standard deviation of all values in a column is not outside the expected range.
`daily_sample_stddev_in_range`	Standard deviation of numeric values is in the range	monitoring	Verifies that the sample standard deviation of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_sample_stddev_in_range`	Standard deviation of numeric values is in the range	monitoring	Verifies that the sample standard deviation of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_sample_stddev_in_range`	Standard deviation of numeric values is in the range	partitioned	Verifies that the sample standard deviation of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_sample_stddev_in_range`	Standard deviation of numeric values is in the range	partitioned	Verifies that the sample standard deviation of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

population stddev in range

This check calculates the population standard deviation of numeric values. It verifies that the population standard deviation is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_population_stddev_in_range`	Population standard deviation of numeric values is in the range	profiling	Verifies that the population standard deviation of all values in a column is not outside the expected range.
`daily_population_stddev_in_range`	Population standard deviation of numeric values is in the range	monitoring	Verifies that the population standard deviation of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_population_stddev_in_range`	Population standard deviation of numeric values is in the range	monitoring	Verifies that the population standard deviation of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_population_stddev_in_range`	Population standard deviation of numeric values is in the range	partitioned	Verifies that the population standard deviation of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_population_stddev_in_range`	Population standard deviation of numeric values is in the range	partitioned	Verifies that the population standard deviation of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

sample variance in range

This check calculates a sample variance of numeric values. It verifies that the sample variance is within the range of accepted values and raises a data quality issue when it is not within a valid range.

Data quality check name	Friendly name	Check type	Description
`profile_sample_variance_in_range`	Variance of numeric values is in the range	profiling	Verifies that the sample variance of all values in a column is not outside the expected range.
`daily_sample_variance_in_range`	Variance of numeric values is in the range	monitoring	Verifies that the sample variance of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_sample_variance_in_range`	Variance of numeric values is in the range	monitoring	Verifies that the sample variance of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_sample_variance_in_range`	Variance of numeric values is in the range	partitioned	Verifies that the sample variance of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_sample_variance_in_range`	Variance of numeric values is in the range	partitioned	Verifies that the sample variance of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

population variance in range

This check calculates a population variance of numeric values. It verifies that the population variance is within the range of accepted values and raises a data quality issue when it is not within a valid range.o

Data quality check name	Friendly name	Check type	Description
`profile_population_variance_in_range`	Population variance of numeric values is in the range	profiling	Verifies that the population variance of all values in a column is not outside the expected range.
`daily_population_variance_in_range`	Population variance of numeric values is in the range	monitoring	Verifies that the population variance of all values in a column is not outside the expected range. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_population_variance_in_range`	Population variance of numeric values is in the range	monitoring	Verifies that the population variance of all values in a column is not outside the expected range. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_population_variance_in_range`	Population variance of numeric values is in the range	partitioned	Verifies that the population variance of all values in a column is not outside the expected range. Stores a separate data quality check result for each daily partition.
`monthly_partition_population_variance_in_range`	Population variance of numeric values is in the range	partitioned	Verifies that the population variance of all values in a column is not outside the expected range. Stores a separate data quality check result for each monthly partition.

invalid latitude

This check finds numeric values that are not valid latitude coordinates. A valid latitude coordinate is in the range -90...90. It counts the values outside a valid range for a latitude. This check raises a data quality issue when the count of invalid values exceeds the maximum accepted count.

Data quality check name	Friendly name	Check type	Description
`profile_invalid_latitude`	Maximum count of rows containing invalid latitude values	profiling	Verifies that the number of invalid latitude values in a column does not exceed the maximum accepted count.
`daily_invalid_latitude`	Maximum count of rows containing invalid latitude values	monitoring	Verifies that the number of invalid latitude values in a column does not exceed the maximum accepted count. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_invalid_latitude`	Maximum count of rows containing invalid latitude values	monitoring	Verifies that the number of invalid latitude values in a column does not exceed the maximum accepted count. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_invalid_latitude`	Maximum count of rows containing invalid latitude values	partitioned	Verifies that the number of invalid latitude values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each daily partition.
`monthly_partition_invalid_latitude`	Maximum count of rows containing invalid latitude values	partitioned	Verifies that the number of invalid latitude values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each monthly partition.

valid latitude percent

This check verifies that numeric values are valid latitude coordinates. A valid latitude coordinate is in the range -90...90. It measures the percentage of values within a valid range for a latitude. This check raises a data quality issue when the rate of valid values is below the minimum accepted percentage.

Data quality check name	Friendly name	Check type	Description
`profile_valid_latitude_percent`	Minimum percentage of rows containing valid latitude values	profiling	Verifies that the percentage of valid latitude values in a column does not fall below the minimum accepted percentage.
`daily_valid_latitude_percent`	Minimum percentage of rows containing valid latitude values	monitoring	Verifies that the percentage of valid latitude values in a column does not fall below the minimum accepted percentage. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_valid_latitude_percent`	Minimum percentage of rows containing valid latitude values	monitoring	Verifies that the percentage of valid latitude values in a column does not fall below the minimum accepted percentage. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_valid_latitude_percent`	Minimum percentage of rows containing valid latitude values	partitioned	Verifies that the percentage of valid latitude values in a column does not fall below the minimum accepted percentage. Stores a separate data quality check result for each daily partition.
`monthly_partition_valid_latitude_percent`	Minimum percentage of rows containing valid latitude values	partitioned	Verifies that the percentage of valid latitude values in a column does not fall below the minimum accepted percentage. Stores a separate data quality check result for each monthly partition.

invalid longitude

This check finds numeric values that are not valid longitude coordinates. A valid longitude coordinate is in the range -180...180. It counts the values outside a valid range for a longitude. This check raises a data quality issue when the count of invalid values exceeds the maximum accepted count.

Data quality check name	Friendly name	Check type	Description
`profile_invalid_longitude`	Maximum count of rows containing invalid longitude values	profiling	Verifies that the number of invalid longitude values in a column does not exceed the maximum accepted count.
`daily_invalid_longitude`	Maximum count of rows containing invalid longitude values	monitoring	Verifies that the number of invalid longitude values in a column does not exceed the maximum accepted count. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_invalid_longitude`	Maximum count of rows containing invalid longitude values	monitoring	Verifies that the number of invalid longitude values in a column does not exceed the maximum accepted count. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_invalid_longitude`	Maximum count of rows containing invalid longitude values	partitioned	Verifies that the number of invalid longitude values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each daily partition.
`monthly_partition_invalid_longitude`	Maximum count of rows containing invalid longitude values	partitioned	Verifies that the number of invalid longitude values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each monthly partition.

valid longitude percent

This check verifies that numeric values are valid longitude coordinates. A valid longitude coordinate is in the range --180...180. It measures the percentage of values within a valid range for a longitude. This check raises a data quality issue when the rate of valid values is below the minimum accepted percentage.

Data quality check name	Friendly name	Check type	Description
`profile_valid_longitude_percent`	Minimum percentage of rows containing valid longitude values	profiling	Verifies that the percentage of valid longitude values in a column does not fall below the minimum accepted percentage.
`daily_valid_longitude_percent`	Minimum percentage of rows containing valid longitude values	monitoring	Verifies that the percentage of valid longitude values in a column does not fall below the minimum accepted percentage. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_valid_longitude_percent`	Minimum percentage of rows containing valid longitude values	monitoring	Verifies that the percentage of valid longitude values in a column does not fall below the minimum accepted percentage. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_valid_longitude_percent`	Minimum percentage of rows containing valid longitude values	partitioned	Verifies that the percentage of valid longitude values in a column does not fall below the minimum accepted percentage. Stores a separate data quality check result for each daily partition.
`monthly_partition_valid_longitude_percent`	Minimum percentage of rows containing valid longitude values	partitioned	Verifies that the percentage of valid longitude values in a column does not fall below the minimum accepted percentage. Stores a separate data quality check result for each monthly partition.

non negative values

This check finds and counts non negative values in a numeric column. It raises a data quality issue when the count of non-negative values is above the maximum accepted count.

Data quality check name	Friendly name	Check type	Description
`profile_non_negative_values`	Maximum count of rows containing non negative values	profiling	Verifies that the number of non-negative values in a column does not exceed the maximum accepted count.
`daily_non_negative_values`	Maximum count of rows containing non negative values	monitoring	Verifies that the number of non-negative values in a column does not exceed the maximum accepted count. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_non_negative_values`	Maximum count of rows containing non negative values	monitoring	Verifies that the number of non-negative values in a column does not exceed the maximum accepted count. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_non_negative_values`	Maximum count of rows containing non negative values	partitioned	Verifies that the number of non-negative values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each daily partition.
`monthly_partition_non_negative_values`	Maximum count of rows containing non negative values	partitioned	Verifies that the number of non-negative values in a column does not exceed the maximum accepted count. Stores a separate data quality check result for each monthly partition.

non negative values percent

This check finds non-negative values in a numeric column. It measures the percentage of non-negative values and raises a data quality issue when the rate of non-negative values exceeds the maximum accepted percentage.

Data quality check name	Friendly name	Check type	Description
`profile_non_negative_values_percent`	Maximum percentage of rows containing non negative values	profiling	Verifies that the percentage of non-negative values in a column does not exceed the maximum accepted percentage.
`daily_non_negative_values_percent`	Maximum percentage of rows containing non negative values	monitoring	Verifies that the percentage of non-negative values in a column does not exceed the maximum accepted percentage. Stores the most recent captured value for each day when the data quality check was evaluated.
`monthly_non_negative_values_percent`	Maximum percentage of rows containing non negative values	monitoring	Verifies that the percentage of non-negative values in a column does not exceed the maximum accepted percentage. Stores the most recent value for each month when the data quality check was evaluated.
`daily_partition_non_negative_values_percent`	Maximum percentage of rows containing non negative values	partitioned	Verifies that the percentage of non-negative values in a column does not exceed the maximum accepted percentage. Stores a separate data quality check result for each daily partition.
`monthly_partition_non_negative_values_percent`	Maximum percentage of rows containing non negative values	partitioned	Verifies that the percentage of non-negative values in a column does not exceed the maximum accepted percentage. Stores a separate data quality check result for each monthly partition.