TRANSFORMATION RULE GENERATION AND VALIDATION

    公开(公告)号:US20210232591A1

    公开(公告)日:2021-07-29

    申请号:US16776407

    申请日:2020-01-29

    Applicant: SAP SE

    Abstract: Transformation rule generation and validation functionality is provided herein. Transformation rules can be generated for one or more mappings in an alignment between a source database and a target database. The transformation rules can transform instance data from the source data model to a form matching the target data model. One or more transformation rules can be generated for a mapping between fields in a source database and a field in a target database. The transformation rules can be generated based on one or more source fields and a target field of a mapping, and one or more identified functions. Evaluating the transformation rules can include generating test data based on the transformation rules applied to instance data from the source database. The test data can be evaluated against instance data from the target database. The transformation rules and the evaluation results can be provided in a user interface.

    Candidate element selection using significance metric values

    公开(公告)号:US11455283B2

    公开(公告)日:2022-09-27

    申请号:US16848463

    申请日:2020-04-14

    Applicant: SAP SE

    Abstract: Techniques and solutions are described for determining a set of elements of a second set that may correspond to a given element of a first set of elements. The elements can be, in specific examples, components of a database system, such as tables (or entities), attributes, or records. Significance metric values are calculated for elements in the first and second sets. The significance metric values can be a number of records in an entity or a number of read or write access operations for an entity or for a record of an entity. A significance metric value for the given element can be used at least in part to select elements of the second set as potential match candidates, based at least in part on significance metric values for elements of the second set. Selecting elements can include selecting elements based on a window of elements of the second set or a range of significance metric values.

    RULE MINING FOR RULE AND LOGIC STATEMENT DEVELOPMENT

    公开(公告)号:US20210073655A1

    公开(公告)日:2021-03-11

    申请号:US16567470

    申请日:2019-09-11

    Applicant: SAP SE

    Abstract: Smart rule development and rule mining functionality is provided herein. Rule mining for use in rule development can include generating logic statement proposals, rule deduplication, and rule template generation. Rule mining can include accessing a rule set to analyze the rule set against an input logic statement to identify existing rules which match at least in part the input logic statement. Rule deduplication can include returning exact rule matches to replace the input logic statement. Proposing logic statements can include returning logically related rules from rules found that include the input logic statement. Generating rule templates can include returning a template based on the entire rule(s) which includes the input logic statement. Ranking scores can be calculated for returned rules, whether for deduplication, proposals, or template generation. The scores can be based on statistical information for the rules, such as usage of the rule or coverage of the rule.

    Transformation rule generation and validation

    公开(公告)号:US11593392B2

    公开(公告)日:2023-02-28

    申请号:US16776407

    申请日:2020-01-29

    Applicant: SAP SE

    Abstract: Transformation rule generation and validation functionality is provided herein. Transformation rules can be generated for one or more mappings in an alignment between a source database and a target database. The transformation rules can transform instance data from the source data model to a form matching the target data model. One or more transformation rules can be generated for a mapping between fields in a source database and a field in a target database. The transformation rules can be generated based on one or more source fields and a target field of a mapping, and one or more identified functions. Evaluating the transformation rules can include generating test data based on the transformation rules applied to instance data from the source database. The test data can be evaluated against instance data from the target database. The transformation rules and the evaluation results can be provided in a user interface.

    CANDIDATE ELEMENT SELECTION USING SIGNIFICANCE METRIC VALUES

    公开(公告)号:US20210318995A1

    公开(公告)日:2021-10-14

    申请号:US16848463

    申请日:2020-04-14

    Applicant: SAP SE

    Abstract: Techniques and solutions are described for determining a set of elements of a second set that may correspond to a given element of a first set of elements. The elements can be, in specific examples, components of a database system, such as tables (or entities), attributes, or records. Significance metric values are calculated for elements in the first and second sets. The significance metric values can be a number of records in an entity or a number of read or write access operations for an entity or for a record of an entity. A significance metric value for the given element can be used at least in part to select elements of the second set as potential match candidates, based at least in part on significance metric values for elements of the second set. Selecting elements can include selecting elements based on a window of elements of the second set or a range of significance metric values.

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