KEVIN BEYER
Cosmetology in San Francisco, CA
License number
Massachusetts 5003618
Issued Date
May 12, 1986
Expiration Date
Dec 31, 1986
Type
Demonstrator Type 5
Address
Address
San Francisco, CA 94104
Professional information
Principal Architect At Platfora
Position:
Principal Architect at Platfora
Location:
San Francisco Bay Area
Industry:
Computer Software
Work:
Platfora
since Oct 2011
-
Principal Architect
IBM Almaden Research Center
Aug 2000 - Oct 2011
-
Research Staff Member
University of Wisconsin - Madison
1993 - 2000
-
Research Assistant
Education:
University of Wisconsin-Madison 1993 - 2002
Ph.D., Computer Science, Database Systems
Ph.D., Computer Science, Database Systems
Interest-Driven Business Intelligence Systems And Methods Of Data Analysis Using Interest-Driven Data Pipelines
US Patent:
2013023, Sep 12, 2013
Filed:
Apr 26, 2013
Appl. No.:
13/871717
Inventors:
Benjamin Mark Werther - Burlingame CA, US
Kevin Scott Beyer - San Francisco CA, US
Brian F. Baboock - Palo Alto CA, US
Yewei Zhang - Fremont CA, US
Kevin Scott Beyer - San Francisco CA, US
Brian F. Baboock - Palo Alto CA, US
Yewei Zhang - Fremont CA, US
Assignee:
Platfora, Inc. - San Mateo CA
International Classification:
G06F 17/30
US Classification:
707602, 707812
Abstract:
Interest-driven Business Intelligence (BI) systems in accordance with embodiments of the invention are illustrated. In one embodiment of the invention, a data processing system includes raw data storage containing raw data, metadata storage containing metadata that describes the raw data, and an interest-driven data pipeline that is automatically compiled to generate reporting data using the raw data, wherein the interest-driven data pipeline is compiled based upon reporting data requirements automatically derived from at least one report specification defined using the metadata.
Interest-Driven Business Intelligence Systems And Methods Of Data Analysis Using Interest-Driven Data Pipelines
US Patent:
2013022, Aug 29, 2013
Filed:
Apr 11, 2013
Appl. No.:
13/861205
Inventors:
Benjamin Mark Werther - Burlingame CA, US
Kevin Scott Beyer - San Francisco CA, US
Brian F. Babcock - Palo Alto CA, US
Yewei Zhang - Fremont CA, US
Kevin Scott Beyer - San Francisco CA, US
Brian F. Babcock - Palo Alto CA, US
Yewei Zhang - Fremont CA, US
Assignee:
Platfora, Inc. - San Mateo CA
International Classification:
G06F 17/30
US Classification:
707602, 707600
Abstract:
Interest-driven Business Intelligence (BI) systems in accordance with embodiments of the invention are illustrated. In one embodiment of the invention, a data processing system includes raw data storage containing raw data, metadata storage containing metadata that describes the raw data, and an interest-driven data pipeline that is automatically compiled to generate reporting data using the raw data, wherein the interest-driven data pipeline is compiled based upon reporting data requirements automatically derived from at least one report specification defined using the metadata.
Interest-Driven Business Intelligence Systems And Methods Of Data Analysis Using Interest-Driven Data Pipelines
US Patent:
8447721, May 21, 2013
Filed:
Feb 29, 2012
Appl. No.:
13/408872
Inventors:
John Glenn Eshleman - Mountain View CA, US
Benjamin Mark Werther - Burlingame CA, US
Kevin Scott Beyer - San Francisco CA, US
Brian F. Babcock - Palo Alto CA, US
Yewei Zhang - Fremont CA, US
Benjamin Mark Werther - Burlingame CA, US
Kevin Scott Beyer - San Francisco CA, US
Brian F. Babcock - Palo Alto CA, US
Yewei Zhang - Fremont CA, US
Assignee:
Platfora, Inc. - San Mateo CA
International Classification:
G06F 17/30
US Classification:
707602, 707737
Abstract:
Interest-driven Business Intelligence (BI) systems in accordance with embodiments of the invention are illustrated. In one embodiment of the invention, a data processing system includes raw data storage containing raw data, metadata storage containing metadata that describes the raw data, and an interest-driven data pipeline that is automatically compiled to generate reporting data using the raw data, wherein the interest-driven data pipeline is compiled based upon reporting data requirements automatically derived from at least one report specification defined using the metadata.
Kevin Beyer
Location:
San Francisco Bay Area
Industry:
Information Technology and Services
Systems And Methods For Highly Parallel Processing Of Parameterized Simulations
US Patent:
2012032, Dec 20, 2012
Filed:
Aug 27, 2012
Appl. No.:
13/595446
Inventors:
Kevin S. Beyer - San Francisco CA, US
Vuk Ercegovac - Campbell CA, US
Peter Haas - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Fei Xu - Bellevue WA, US
Vuk Ercegovac - Campbell CA, US
Peter Haas - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Fei Xu - Bellevue WA, US
Assignee:
INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY
International Classification:
G06F 9/45
US Classification:
703 22
Abstract:
Systems and associated methods for highly parallel processing of parameterized simulations are described. Embodiments permit processing of stochastic data-intensive simulations in a highly parallel fashion in order to distribute the intensive workload. Embodiments utilize methods of seeding records in a database with a source of pseudo-random numbers, such as a compressed seed for a pseudo-random number generator, such that seeded records may be processed independently in a highly parallel fashion. Thus, embodiments provide systems and associated methods facilitating quicker data-intensive simulation by enabling highly parallel asynchronous simulations.
Adaptive Parallel Data Processing
US Patent:
2012031, Dec 6, 2012
Filed:
May 31, 2011
Appl. No.:
13/149312
Inventors:
Andrey Balmin - San Jose CA, US
Kevin Scott Beyer - San Francisco CA, US
Vuk Ercegovac - Campbell CA, US
Rares Vernica - Irvine CA, US
Kevin Scott Beyer - San Francisco CA, US
Vuk Ercegovac - Campbell CA, US
Rares Vernica - Irvine CA, US
Assignee:
INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY
International Classification:
G06F 9/46
US Classification:
718100
Abstract:
Described herein are methods, systems, apparatuses and products for adaptive parallel data processing. An aspect provides providing a map phase in which at least one map function is applied in parallel on different partitions of input data at different mappers in a parallel data processing system; providing a communication channel between mappers using a distributed meta-data store, wherein said map phase comprises mapper data processing adapted responsive to communication with said distributed meta-data store; and providing data accessible by at least one reduce phase node in which at least one reduce function is applied. Other embodiments are disclosed.
Indexing And Searching Json Objects
US Patent:
8260784, Sep 4, 2012
Filed:
Feb 13, 2009
Appl. No.:
12/371005
Inventors:
Kevin Scott Beyer - San Francisco CA, US
Jun Rao - San Jose CA, US
Eugene J Shekita - San Jose CA, US
Jun Rao - San Jose CA, US
Eugene J Shekita - San Jose CA, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 7/00
US Classification:
707742, 707791, 707797, 715200, 715234
Abstract:
Disclosed is a method of encoding JavaScript Object Notation (JSON) documents in an inverted index, wherein a tree representation of a JSON document is first generated, and, next, the JSON document is shredded into a list of tuples for each atom node, n, in the tree, where value is a label associated with n, path is a concatenation of node labels associated with ancestors of n, type is a description of a type of value, and jdewey of n is a partial Dewey code of its closest ancestor array node, if one exists, or empty, otherwise. Lastly, an inverted index is built using as index term, and jdewey as payload. A method is also described to search the inverted index.
Systems And Methods For Highly Parallel Processing Of Parameterized Simulations
US Patent:
2011032, Dec 29, 2011
Filed:
Jun 29, 2010
Appl. No.:
12/826077
Inventors:
Kevin S. Beyer - San Francisco CA, US
Vuk Ercegovac - Campbell CA, US
Peter Haas - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Fei Xu - Bellevue WA, US
Vuk Ercegovac - Campbell CA, US
Peter Haas - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Fei Xu - Bellevue WA, US
Assignee:
INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY
International Classification:
G06F 9/45
US Classification:
703 22
Abstract:
Systems and associated methods for highly parallel processing of parameterized simulations are described. Embodiments permit processing of stochastic data-intensive simulations in a highly parallel fashion in order to distribute the intensive workload. Embodiments utilize methods of seeding records in a database with a source of pseudo-random numbers, such as a compressed seed for a pseudo-random number generator, such that seeded records may be processed independently in a highly parallel fashion. Thus, embodiments provide systems and associated methods facilitating quicker data-intensive simulation by enabling highly parallel asynchronous simulations.