Microsoft Technology Licensing, LLC

Oleg Ovanesyan

Rahul Kapoor

Jason Todd Henderson

Parul Manek

David Claux

Oleg Ouliankine

Burra Gopal

Andrew Salamatov

Rolando Jimenez Salgado

Warren Randall Byrne

Patrick Michael Conlan

Carlos Brito

Sudhakar Pasupuleti

Sandhya D Jain

Alexandru Croicu

Rakesh Gupta

Steve Clagg

Yilei Wang

Peiwei Cao

Altaf A Gilani

John P Burrows

Ben Sack

Muthiah K Annamalai

Sharon E Edelstein

Denise A La Rue

Christoph Schuler

Thomas A J Mechelke

A web extension is managed through a manifest file. An application managing the web extension receives attributes of the extension from a developer or metadata of the extension. A pointer to the web extension is inserted into the attributes. The pointer can be used as a link to activate the web extension. The attributes are stored in a manifest file formatted in extensible markup language (XML). The functionality of the web extension is managed based on the manifest file.

Managing web extension through manifest file

Methods, systems, and computer program products detect and manage changes in business data integration (BDI) solutions. BDI solutions include extracting, mapping, or loading source information from disparate sources as targets presented to business applications that consume targets. A method involves detecting changes in a BDI solution, classifying each of the changes based on change severity, analyzing what objects would be impacted by the changes, determining whether the objects impacted by the changes can be change handled without user intervention, and change handling without user intervention all the objects impacted by changes that are not severe. Still further, the method involves committing changes to a metadata repository and creating a deployable checkpoint of the metadata repository where the deployable checkpoint is consistent for all the changes handled in the BDI solution. The modularized metadata describes an end-to-end information flow and underlying dependencies between the source information, mappings, targets and business applications.

Detecting and managing changes in business data integration solutions

Extraction of data employing a sequence of remote function calls in form of a synchronous multi-batch call chain is provided. Sequencing of calls is enabled by generating parameters associated with the extraction of a next batch of data. The parameterized, dynamic generation of queries allows for optimization of memory utilization by batching result sets and data conversion. Each subsequent call retrieves a packet of data, picking up where the previous call left off without an overlap. Parameters are updated after each call based on extracted data, available memory, and the like.

Scalable data extraction from data stores

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Oleg Ovanesyan