Abstract: In an example embodiment, a method of automatically generating data validation rules from data stored in a column of a table is provided. Outliers for the data are determined by analyzing a profiling statistic for the data, the profiling statistic having a type. Then it is determined if a predefined limit is exceeded, based on a quantity of the outliers determined for the data through the analysis of the profiling statistic. A data validation rule is then automatically generated based on non-outliers detected in the data through the analysis of the profiling statistic, the generated data validation rule also being based on the type of the profiling statistic. The data validation rule can then be applied to data subsequently entered for the column, causing at least a portion of the data subsequently entered for the column to be rejected.

Abstract: In an example embodiment, a method of automatically generating data validation rules from data stored in a column of a table is provided. Outliers for the data are determined by analyzing a profiling statistic for the data, the profiling statistic having a type. Then it is determined if a predefined limit is exceeded, based on a quantity of the outliers determined for the data through the analysis of the profiling statistic. A data validation rule is then automatically generated based on non-outliers detected in the data through the analysis of the profiling statistic, the generated data validation rule also being based on the type of the profiling statistic. The data validation rule can then be applied to data subsequently entered for the column, causing at least a portion of the data subsequently entered for the column to be rejected.