Aggregation and generation of confidential data insights with confidence values

A computerized method comprising:

• retrieving a plurality of previously submitted confidential data values of a first confidential data type for a slice having one or more attributes;
• for a confidential data type in the submitted confidential data values:
• excluding one or more submitted confidential data values of the confidential data type from the slice that are considered outliers based on an external data set;
• excluding one or more submitted confidential data values of the confidential data type from the slice that are considered outliers based on an internal data set;
• calculating a confidence score for the confidential data type in the slice by multiplying a support score for the confidential data type in the slice by a non-outlier score for the confidential data type in the slice, the support score being equal to n′/(n′+c), where c is a smoothing constant and n′ is the number of non-excluded submitted confidential data values of the confidential data type in the slice and the non-outlier score being equal to n′/n, where n is the total number of non-null submitted confidential data value of the confidential data type in the slice;
• determining whether the confidence score for the confidential data type in the slice exceeds a predetermined threshold;
• and
• in response to a determination that the confidence score for the confidential data type in the slice exceeds the predetermined threshold, permitting computation of one or more insight statistics for the confidential data type for non-excluded submitted confidential data values in the slice.

A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform operations comprising:

• retrieving a plurality of previously submitted confidential data values of a first confidential data type for a slice having one or more attributes;
• for a confidential data type in the submitted confidential data values:
• excluding one or more submitted confidential data values of the confidential data type from the slice that are considered outliers based on an external data set;
• excluding one or more submitted confidential data values of the confidential data type from the slice that are considered outliers based on an internal data set;
• calculating a confidence score for the confidential data type in the slice by multiplying a support score for the confidential data type in the slice by a non-outlier score for the confidential data type in the slice, the support score being equal to n′/(n′+c), where c is a smoothing constant and n′ is the number of non-excluded submitted confidential data values of the confidential data type in the slice and the non-outlier score being equal to n′/n, where n is the total number of non-null submitted confidential data value of the confidential data type in the slice;
• determining whether the confidence score for the confidential data type in the slice exceeds a predetermined threshold;
• and
• in response to a determination that the confidence score for the confidential data type in the slice exceeds the predetermined threshold, permitting computation of one or more insight statistics for the confidential data type for non-excluded submitted confidential data values in the slice.