Teachers Insurance and Annuity Association of America

Daniel R Hursh

Alexis Salvatore Pecoraro

John V Hintze

Edward J Miller, Jr

Pankaj Agrawal

James G Rauscher

Sheppard David Narkier

Gregory Bernard Bahns

Gregory B Bahns

A curated portable datamart system, method, and apparatus are provided. The method, implemented by one or more processors, comprises: inputting, via an application programming interface (API), a client query of a client, the client query requesting a temporal output able to be calculated by individual-specific raw data identifiable within the raw data of a virtual raw datamart; invoking a security and client context layer to authorize the client to access the individual-specific raw data that is specific to the client query; responsive to authorizing the client query, invoking a semantic layer to retrieve the individual-specific raw data from the virtual raw datamart, and curate the individual-specific raw data to generate a curated data deliverable, the curated data deliverable comprising temporal data generated from one or more raw data items accessed by the semantic layer from the virtual raw datamart; and outputting, via the API, the curated data deliverable.

Curated portable datamart

Disclosed are methods and systems for model-based data transformation. An example method includes: receiving a source graph model describing a source data structure, wherein the source graph model comprises a source root node associated with a plurality of source section nodes, wherein each source section node of the plurality of source section nodes is associated with at least one source attribute node; receiving a target graph model describing a target data structure, wherein the target graph model comprises a target root node associated with a plurality of target section nodes, wherein each target section node of the plurality of target section nodes is associated with at least one target attribute node; receiving a transformation map associating a target attribute node of the target data structure with one or more source attribute nodes of the source data structure; extracting, from the source data structure, one or more source data items associated with the one or more source attribute nodes; generating, by applying a transformation specified by the transformation map to the one or more source data items, a target data item associated with the target attribute node; and storing the target data item in the target data structure.

Model-based data transformation

Disclosed are methods and systems for automatically configuring financial product offerings. An example method includes: receiving, by a computer system, a graph model representing a plurality of permutations of definition provisions of a financial product; translating at least a subset of the graph model into definitions of a plurality of business objects; translating the definitions of the plurality of business objects into definitions of a plurality of services to be implemented by an offering of the financial product; receiving, via a user interface, a plurality of service configuration options; applying the plurality of service configuration options to the definitions of the plurality of services; and generating, based on the definitions of the plurality of services, service configuration data for the offering of the financial product.

Model-based configuration of financial product offerings

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Dayton, OH, United States of America

Daniel R Hursh