David C Allan

US Patent:

20200241854, Jul 30, 2020

Filed:

Apr 10, 2020

Appl. No.:

16/845738

Inventors:

- Redwood Shore CA, US
Hassan Heidari Namarvar - Mountain View CA, US
David Allan - Novato CA, US
Ganesh Seetharaman - Redwood Shores CA, US

International Classification:

G06F 8/41
G06N 20/00
G06F 16/14
G06F 16/21
G06F 16/25
G06F 16/435
G06F 16/23
G06N 5/04
G06Q 10/06
G06F 40/30
G06F 3/0482
G06F 17/18
G06N 5/02
G06F 8/10
G06F 8/34
G06F 3/042
G06F 3/06

Abstract:

In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can perform an ontology analysis of a schema definition, to determine the types of data, and datasets or entities, associated with that schema; and generate, or update, a model from a reference schema that includes an ontology defined based on relationships between datasets or entities, and their attributes. A reference HUB including one or more schemas can be used to analyze data flows, and further classify or make recommendations such as, for example, transformations enrichments, filtering, or cross-entity data fusion of an input data.

US Patent:

20200125540, Apr 23, 2020

Filed:

Oct 17, 2019

Appl. No.:

16/656372

Inventors:

- Redwood Shores CA, US
Arun Patnaik - Fremont CA, US
David Allan - Novato CA, US
Frank Joseph Klein - Eagan MN, US
Sathish Paul Leo - San Mateo CA, US
Vikas Varma - Alpharetta GA, US

Assignee:

Oracle International Corporation - Redwood Shores CA

International Classification:

G06F 16/21
G06F 16/25
G06F 9/54

Abstract:

Techniques describes herein updating pipeline flows in within data systems to maintain data integrity and consistency without manual curation. In certain embodiments, data integration system may detect and/or receive indications of a schema change within a source system of the data integration system. One or more data objects affected by the schema change may be identified, and a set of pipeline rules may be invoked for each of the affected schema changes. The pipeline rules may define a single transformation or a multi-step transformation process by which the data in the source system is provided to one or more target systems. After applying the pipeline rules to the updated source schema, the data received from the source system may be processed using the updated pipeline rules, transformed, and transmitted to the target system(s) to maintain the data integrity of the system.

US Patent:

20180052870, Feb 22, 2018

Filed:

Aug 22, 2017

Appl. No.:

15/683559

Inventors:

- Redwood Shores CA, US
Hassan Heidari Namarvar - Mountain View CA, US
David Allan - Novato CA, US
Ganesh Seetharaman - Redwood Shores CA, US

International Classification:

G06F 17/30
G06N 99/00
G06N 5/04

Abstract:

In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can perform an ontology analysis of a schema definition, to determine the types of data, and datasets or entities, associated with that schema; and generate, or update, a model from a reference schema that includes an ontology defined based on relationships between datasets or entities, and their attributes. A reference HUB including one or more schemas can be used to analyze data flows, and further classify or make recommendations such as, for example, transformations enrichments, filtering, or cross-entity data fusion of an input data.

US Patent:

20140344210, Nov 20, 2014

Filed:

Oct 2, 2013

Appl. No.:

14/044417

Inventors:

- Redwood Shores CA, US
David Allan - Mountain View CA, US
Kwok-hung (Thomas) Lau - Los Altos CA, US

Assignee:

Oracle International Corporation - Redwood Shores CA

International Classification:

G06F 17/30

US Classification:

707602

Abstract:

A data integration system is disclosed that incorporates one or more techniques for simplifying the design and maintenance of a mapping. As components are added or removed to an existing design, the data integration system removes the need to specify all input and output attributes. In one aspect, components types are implemented that allow assignment expressions to reference all or part of upstream components. Therefore, attributes of certain types of components can be propagated to downstream components or otherwise inherited from upstream components with minimal effort on the part of a map designer. During code generation the attributes required to be projected by any component can be derived based on the needs of the downstream components.

US Patent:

20140344310, Nov 20, 2014

Filed:

Nov 11, 2013

Appl. No.:

14/077140

Inventors:

- Redwood Shores CA, US
David Allan - Mountain View CA, US
John Leigh - San Mateo CA, US
Thomas Lau - Mountain View CA, US
Joseph F. Klein - Eagan MN, US

Assignee:

Oracle International Corporation - Redwood Shores CA

International Classification:

G06F 17/30

US Classification:

707803

Abstract:

In various embodiments, a data integration system is disclosed which enables users to create a logical design which is platform and technology independent. The user can create a logical design that defines, at a high level, how a user wants data to flow between sources and targets. The tool can analyze the logical design, in view of the user's infrastructure, and create a physical design. The logical design can include a plurality of components corresponding to each source and target in the design, as well as operations such as joins or filters, and access points. Each component when transferred to the physical design generates code to perform operations on the data. Depending on the underlying technology (e.g., SQL Server, Oracle, Hadoop, etc.) and the language used (SQL, pig, etc.) the code generated by each component may be different.