Abstract: Techniques and solutions are described for identifying data, such as records in a relational database. The data can have a first plurality of attributes, a second plurality of which are used to create the identifier. The identifier can be included as a column in a data structure in which the data is stored, such as a column in a table storing a record. The disclosed data identifiers can provide semantically meaningful information. The disclosed identifiers can also improve data store performance, such as by facilitating data retrieval, and helping to guard against inserting duplicate entries in the data store.

Abstract: Techniques and solutions are described for identifying data, such as records in a relational database. The data can have a first plurality of attributes, a second plurality of which are used to create the identifier. The identifier can be included as a column in a data structure in which the data is stored, such as a column in a table storing a record. The disclosed data identifiers can provide semantically meaningful information. The disclosed identifiers can also improve data store performance, such as by facilitating data retrieval, and helping to guard against inserting duplicate entries in the data store.

Abstract: Automatic rule generation is provided herein for generating data mapping, data transformation, or process flow rules or logic statements. The rules may be generated based on a field or attribute, and may be further based on a partial rule or one or more existing rules, or a combination thereof. Proposed rules may be generated based on analysis of a data set, including identifying possible values for the attribute and to calculate scores for the possible values. A score may be the probability of the value based on the data set. The data set may be cleaned or scrubbed based on the partial rule or existing rules. The proposed rules may be provided to a user, or may be automatically selected. Rule generation may include constraint checking. Constraint checking may include detecting empty data sets or detecting when two rules are not mutually exclusive.