Microsoft Technology Licensing, LLC

Srinivasa Rao Burugapalli

Alexander Vaschillo

Chris A Suver

Andrew Conrad

Luca Bolognese

Todd F Pfleiger

Bertan Ari

Avner Y Aharoni

Christopher Allen Suver

Michael Lee Brundage

David N Schach

Michael Rys

Murray K Low

Steven D White

Jagan M Peri

Adam Wiener

Aaron David Cottle

Alex Laskos

Jason Zhengnan Zhu

Ilker Cengiz

Bruno Denuit

Veerendra K Koya

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.

Extract, transform and load using metadata

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.

Mapping architecture for arbitrary data models

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.

System and method for viewing relational data using a hierarchical schema

Users and programmers can load semi-structured hierarchical data, such as XML data, of arbitrary size and structure into 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. The hierarchical data is streamed into the relational database tables in a single operation.

System and method for loading hierarchical data into relational database systems

The present invention relates to a system and methodology to facilitate data communications and data management between network entities operating in accordance with various data structures and operating environments. A managed class of application programming interfaces (API) are provided that support data communications between remote/local locations employing a first data structure and a second location supporting a second data structure (e.g., API for NET languages to access SQL Server via XML views). The managed class and associated APIs provide data transformations between such structures to facilitate communications and data management among various locations and architectures. In addition, the managed class and APIs facilitate operations between disparate object systems such as between managed and unmanaged object systems via interface support of a wrapper and associated marshalling technologies to bridge communications between such systems.

System and method providing API interface between XML and SQL while interacting with a managed object environment

Growing community of inventors

Sammamish, WA, United States of America

Srinivasa Rao Burugapalli