Patents by Inventor Umamaheswari Kathirvel

Umamaheswari Kathirvel has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10824624
    Abstract: Embodiments of the invention enable analyzing, optimizing and remediating a proposed data query prior to query implementation. Embodiments receive a request from a user; in response, perform an initialization comprising connecting to a data management structure; exporting an explain text of the request in a known format; and disconnecting from the data management structure. In response to initialization, embodiments perform a shredding step comprising shredding the explain text of the request; and populating a plurality of metadata tables comprising a superset table required for internal processing. Next, embodiments define or redefine a machine learning algorithm comprising a plurality of rulesets by calling a plurality of macros to act on the request; access a historic log comprising identified performance tuning parameters configured for tuning queries; and use the identified performance tuning parameters and the machine learning algorithm, optimize the query, thereby resulting in an optimized query.
    Type: Grant
    Filed: July 12, 2018
    Date of Patent: November 3, 2020
    Assignee: BANK OF AMERICA CORPORATION
    Inventors: Umamaheswari Kathirvel, Srikanth Padmanabhan
  • Publication number: 20200019633
    Abstract: Embodiments of the invention enable analyzing, optimizing and remediating a proposed data query prior to query implementation. Embodiments receive a request from a user; in response, perform an initialization comprising connecting to a data management structure; exporting an explain text of the request in a known format; and disconnecting from the data management structure. In response to initialization, embodiments perform a shredding step comprising shredding the explain text of the request; and populating a plurality of metadata tables comprising a superset table required for internal processing. Next, embodiments define or redefine a machine learning algorithm comprising a plurality of rulesets by calling a plurality of macros to act on the request; access a historic log comprising identified performance tuning parameters configured for tuning queries; and use the identified performance tuning parameters and the machine learning algorithm, optimize the query, thereby resulting in an optimized query.
    Type: Application
    Filed: July 12, 2018
    Publication date: January 16, 2020
    Inventors: Umamaheswari Kathirvel, Srikanth Padmanabhan