Fair Isaac Corporation

Capillary Technologies International Pte Ltd

Prasun Kumar

Stuart L Crawford

Navin Doshi

Sergei Tolmanov

Michael Steele

Kashyap Babu Rao Kolipaka

Megan Thorsen

Xing Zhao

Krishna Kumar Mehra

Chris Erickson

Sudipta Samanta

Richard Schiffman

Pravanjan Choudhury

Abhilash L Lakkur

An ETL system for extracting transactional data from a plurality of source machines is provided. The ETL system includes a data query module configured to provide an interface to enable a data analyst to define an input query to extract transactional data, which is present on a plurality of source machines. The source machines form a multi-tenant system and each source machine is identified by a unique tenant identifier. The system also includes a query parsing module coupled to the data query module and configured to deconstruct the input query to create a tree structure. The tree structure comprises a plurality of distinct queries. The system further includes a data extraction module coupled to the query parsing module and configured to extract transactional data based on the distinct queries and copy the transactional data to a destination system wherein the transactional data comprises a plurality of data types.

Extract, transform and load (ETL) system and method

A tree structure of plurality of information records arranged is recursively grown by splitting at least a portion of the records and by generating at least one predictive model. Related apparatus, systems, methods and computer program products are also described.

Automating growth and evaluation of segmentation trees

Data characterizing a desired variable order and an unordered graph can be received so that all paths in the unordered graph can be enumerated and a first path in the unordered graph can be leveled according to the desired variable order in a first oblivious read once decision graph. For each additional path other than the first path, the additional path is leveled in the desired order, nodes of the additional path are added to the first oblivious read once decision graph, and a union operation is performed on the first oblivious read once decision graph to union graph roots on the first oblivious read once decision graph. Thereafter, generation of a second oblivious read once decision graph can be initiated after completing processing of the first path and each additional path. Related apparatus, systems, techniques and articles are also described.

Converting unordered graphs to oblivious read once ordered graph representation

Data characterizing a plurality of related action graphs is received. Thereafter, the plurality of related action graphs are transformed into a logically equivalent structure so that rendering of the logically equivalent structure can be initiated. Related interfaces, apparatus, systems, techniques and articles are also described.

Construction of decision logic with graphs

Techniques are described for logically comparing strategies. In one aspect the strategies can be compared by receiving a request to compare a first strategy to a second strategy, the first strategy graphically represented by a first set of linked nodes, the second strategy graphically represented by a second set of linked nodes, each set of linked nodes linking a root node to at least one action node; identifying a subset of linked nodes from at least one of the first set of linked nodes and the second set of linked nodes based on an equivalence of a first subset of the first set of linked nodes to a second subset of the second set of linked nodes; and, providing a visual depiction of the identified subset of the linked nodes to a user, the visual depiction corresponding to the equivalence of the first subset to the second subset.

Decision logic comparison and review

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Bengaluru, India

Prasun Kumar