Abstract: The extract and transformation operation performed on multiple data sources. In the extract operation, a computing system periodically performs an extraction operation on the data sources, perhaps as defined by metadata. The transformation operation is performed on at least some the extracted data, and is periodically performed, perhaps also in a manner that is defined by metadata. When performing each iteration of the transformation operation, the computing system performs a transformation operation on valid data, marks other data as suspect (due to a dependency on data that is not present), and completes transformation on yet other data that had previously been marked as suspect or perhaps reaffirms its suspect status if the needed data is still not available.

Abstract: The extract and transformation operation performed on multiple data sources. In the extract operation, a computing system periodically performs an extraction operation on the data sources, perhaps as defined by metadata. The transformation operation is performed on at least some the extracted data, and is periodically performed, perhaps also in a manner that is defined by metadata. When performing each iteration of the transformation operation, the computing system performs a transformation operation on valid data, marks other data as suspect (due to a dependency on data that is not present), and completes transformation on yet other data that had previously been marked as suspect or perhaps reaffirms its suspect status if the needed data is still not available.

Abstract: A data mapping architecture for mapping between two or more data sources without modifying the metadata or structure of the data sources themselves. Data mapping also supports updates. The architecture also supports at least the case where data sources that are being mapped, are given, their schemas predefined, and cannot be changed. The architecture includes a mapping component that receives respective metadata from at least two arbitrary data models, and maps expressions between the data models.

Abstract: Users and programmers view relational database tables using an schema such as an SQL-annotated XML schema. The schema describes how XML data maps into base tables and fields, including complex one-to-many and many-to-many relationships.

Abstract: Users and programmers view relational database tables using an schema such as an SQL-annotated XML schema. The schema describes how XML data maps into base tables and fields, including complex one-to-many and many-to-many relationships.