CLUSTERING WITHIN DATABASE DATA MODELS
    41.
    发明申请

    公开(公告)号:US20200349128A1

    公开(公告)日:2020-11-05

    申请号:US16399363

    申请日:2019-04-30

    Applicant: SAP SE

    Abstract: A method for data model clustering is provided herein. A first representation of a data model may be received. Edge betweenness values may be determined for respective nodes in the first representation. At least one node in the first representation may be identified as a linking node based on the respective edge betweenness values. One or more linking nodes may be removed from the first representation, thereby forming at least a first cluster and a second cluster. Degrees for the respective remaining nodes may be calculated. Respective hub nodes may be identified for the respective clusters based on the respective degrees in the clusters. Respective descriptions may be generated for the respective clusters based on the respective hub nodes. A clustered representation of the first representation may be stored with the clusters and their respective descriptions.

    Relationship analysis using vector representations of database tables

    公开(公告)号:US12235822B2

    公开(公告)日:2025-02-25

    申请号:US18410250

    申请日:2024-01-11

    Applicant: SAP SE

    Abstract: A computer-implemented method includes representing a plurality of database tables as respective vectors in a multi-dimensional vector space, receiving an indication that a first database table represented by a first vector and a second database table represented by a second vector are related to each other, moving positions of the respective vectors representing the plurality of database tables in the multi-dimensional vector space in response to the indication, and grouping the plurality of database tables into one or more table clusters based on positions of the respective vectors representing the plurality of database tables in the multi-dimensional vector space.

    INTELLIGENT UPDATE OF APPLICATION PROGRAMMING INTERFACES

    公开(公告)号:US20250028518A1

    公开(公告)日:2025-01-23

    申请号:US18357023

    申请日:2023-07-21

    Applicant: SAP SE

    Abstract: A computer-implemented method can specify a source version and a target version of an application programming interface (API) and a target programming language; and retrieve a difference graph connecting from a source knowledge graph characterizing the source version of the API to a target knowledge graph characterizing the target version of the API. The difference graph includes one or more revision edges representing changes of the API between the source version and the target version. The method can install one or more function packages written in the target programming language and associated with the one or more revision edges; and run the one or more function packages to update the API from the source version to the target version.

    MESSAGE-BASED MANAGEMENT OF KNOWLEDGE GRAPHS REPRESENTING APPLICATION PROGRAMMING INTERFACES

    公开(公告)号:US20240296079A1

    公开(公告)日:2024-09-05

    申请号:US18116750

    申请日:2023-03-02

    Applicant: SAP SE

    CPC classification number: G06F9/541 G06F8/71

    Abstract: A computer-implemented method can include registering a new version of an application programming interface (API) with an API registry, transforming the new version of the API to a first knowledge graph, comparing the first knowledge graph to a second knowledge graph to determine a difference graph, and sending the difference graph to selected entities who have subscribed to the API registry. The second knowledge graph can be transformed from a prior version of the application programming interface. The difference graph connects the second knowledge graph to the first knowledge graph and identifies changes from the second knowledge graph to the first knowledge graph.

    Automatic conversion of data models using data model annotations

    公开(公告)号:US11762820B2

    公开(公告)日:2023-09-19

    申请号:US17887267

    申请日:2022-08-12

    Applicant: SAP SE

    CPC classification number: G06F16/212 G06F16/213 G06F16/2282 G06F16/288

    Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.

    Metadata object identifier registry

    公开(公告)号:US11755591B2

    公开(公告)日:2023-09-12

    申请号:US17395901

    申请日:2021-08-06

    Applicant: SAP SE

    CPC classification number: G06F16/24573 G06F16/2365 G06F16/38

    Abstract: Various examples are directed to systems and methods for administering data model metadata for a plurality of data models. A metadata service may receive a first retrieval request from a requesting system. The first retrieval request may comprise an indication of a first local object identifier referencing a definition of a first local object from a first data model and an indication of a target data model. The metadata service may retrieve a first record from a metadata identifier registry, where the first record comprises an indication of the first local object identifier and an indication of a first global object identifier corresponding to the first local object identifier. The metadata service may determine a second local object identifier referencing a definition of a second local object identifier referencing a definition of a second local object in the target data model and return the second local object identifier.

    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.

    METADATA OBJECT IDENTIFIER REGISTRY

    公开(公告)号:US20230047681A1

    公开(公告)日:2023-02-16

    申请号:US17395901

    申请日:2021-08-06

    Applicant: SAP SE

    Abstract: Various examples are directed to systems and methods for administering data model metadata for a plurality of data models. A metadata service may receive a first retrieval request from a requesting system. The first retrieval request may comprise an indication of a first local object identifier referencing a definition of a first local object from a first data model and an indication of a target data model. The metadata service may retrieve a first record from a metadata identifier registry, where the first record comprises an indication of the first local object identifier and an indication of a first global object identifier corresponding to the first local object identifier. The metadata service may determine a second local object identifier referencing a definition of a second local object identifier referencing a definition of a second local object in the target data model and return the second local object identifier.

    AUTOMATIC CONVERSION OF DATA MODELS USING DATA MODEL ANNOTATIONS

    公开(公告)号:US20220391363A1

    公开(公告)日:2022-12-08

    申请号:US17887267

    申请日:2022-08-12

    Applicant: SAP SE

    Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.

    Automatic conversion of data models using data model annotations

    公开(公告)号:US11442907B2

    公开(公告)日:2022-09-13

    申请号:US16780481

    申请日:2020-02-03

    Applicant: SAP SE

    Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.

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