Supporting combination of flow based ETL and entity relationship based ETL
First Claim
1. A method for generating a data integration scenario between a data source and a data target using a combination of a data flow extract-transform-load (ETL) and an entity relationship extract-transform-load (ETL), the method comprising:
- receiving, at one or more computer systems, a set of extract-transform-load (ETL) entity relationships defined via a component of a logical design of the data integration scenario, the set of ETL entity relationships having a relationship defined between one or more attributes of a first entity in a dataset and one or more attributes of a second entity in the dataset;
automatically determining, with one or more processors associated with the one or more computer systems, an extract-transform-load (ETL) data flow model using the set of ETL entity relationships, wherein the ETL data flow model is configured to provide semantic definitions for the logical design, wherein the semantic definitions define entity relationships in the dataset that identify how columns of the data target are populated from attributes of the data source and from one of the one or more attributes of the first entity in the dataset and the one or more attributes of the second entity in the dataset; and
generating, with the one or more processors associated with the one or more computer systems, information indicative of the ETL data flow model in a view of the logical design, wherein a set of attributes are exposed to downstream components of the logical design that includes the one or more attributes of the first entity and the one or more attributes of the second entity.
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Abstract
A data integration system is disclosed that incorporates one or more techniques for eases the design and maintenance of a mapping. As components are added to an existing design, the data integration system removes the need to specify all input and output attributes. In one aspect, components types are implement that allow entity relationships to be added and/or edited in a flow view of a logical design. Therefore, attributes of components representing datasets can be added and propagated to downstream components with minimal effort on the part of a map designer.
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Citations
25 Claims
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1. A method for generating a data integration scenario between a data source and a data target using a combination of a data flow extract-transform-load (ETL) and an entity relationship extract-transform-load (ETL), the method comprising:
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receiving, at one or more computer systems, a set of extract-transform-load (ETL) entity relationships defined via a component of a logical design of the data integration scenario, the set of ETL entity relationships having a relationship defined between one or more attributes of a first entity in a dataset and one or more attributes of a second entity in the dataset; automatically determining, with one or more processors associated with the one or more computer systems, an extract-transform-load (ETL) data flow model using the set of ETL entity relationships, wherein the ETL data flow model is configured to provide semantic definitions for the logical design, wherein the semantic definitions define entity relationships in the dataset that identify how columns of the data target are populated from attributes of the data source and from one of the one or more attributes of the first entity in the dataset and the one or more attributes of the second entity in the dataset; and generating, with the one or more processors associated with the one or more computer systems, information indicative of the ETL data flow model in a view of the logical design, wherein a set of attributes are exposed to downstream components of the logical design that includes the one or more attributes of the first entity and the one or more attributes of the second entity. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A non-transitory computer-readable medium storing computer-executable code for generating a data integration scenario between a data source and a data target using a combination of a data flow extract-transform-load (ETL) and an entity relationship extract-transform-load (ETL), the non-transitory computer-readable medium comprising:
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code for receiving a set of extract-transform-load (ETL) entity relationships defined via a component of a logical design of the data integration scenario, the set of ETL entity relationships having a relationship defined between one or more attributes of a first entity in a dataset and one or more attributes of a second entity in the dataset; code for automatically determining an extract-transform-load (ETL) data flow model using the set of ETL entity relationships, wherein the ETL data flow model is configured to provide semantic definitions for the logical design, wherein the semantic definitions define entity relationships in the dataset that identify how columns of the data target are populated from attributes of the data source and from one of the one or more attributes of the first entity in the dataset and the one or more attributes of the second entity in the dataset; and code for generating information indicative of the ETL data flow model in a view of the logical design, wherein a set of attributes are exposed to downstream components of the logical design that includes the one or more attributes of the first entity and the one or more attributes of the second entity. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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19. A system for generating a data integration scenario between a data source and a data target using a combination of a data flow extract-transform-load (ETL) and an entity relationship extract-transform-load (ETL), the system comprising:
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a processor; and a memory storing instructions which when executed by the processor configure the processor to; receive a set of extract-transform-load (ETL) entity relationships defined via a component of a logical design of the data integration scenario, the set of ETL entity relationships having a relationship defined between one or more attributes of a first entity in a dataset and one or more attributes of a second entity in the dataset; automatically determine an extract-transform-load (ETL) data flow model using the set of ETL entity relationships, wherein the ETL data flow model is configured to provide semantic definitions for the logical design, wherein the semantic definitions define entity relationships in the dataset that identify how columns of the data target are populated from attributes of the data source and from one of the one or more attributes of the first entity in the dataset and the one or more attributes of the second entity in dataset; and generate information indicative of the ETL data flow model in a view of the logical design, wherein a set of attributes are exposed to downstream components of the logical design that includes the one or more attributes of the first entity and the one or more attributes of the second entity. - View Dependent Claims (20, 21, 22, 23, 24, 25)
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Specification