Location History:
- Raleigh, NC (US) (2017)
- Apex, NC (US) (2019 - 2023)
Company Filing History:
Years Active: 2017-2023
Title: Innovations of Charles Michael Cavalier
Introduction
Charles Michael Cavalier is an accomplished inventor based in Apex, NC (US). He has made significant contributions to the field of event stream processing, holding a total of 4 patents. His work focuses on automating data processing models, which enhances the efficiency and effectiveness of data management systems.
Latest Patents
Cavalier's latest patents include "Automated streaming data model generation with parallel processing capability." This invention describes a method where an event stream processing (ESP) model is utilized to read computational processes. The process involves receiving an event block object, extracting measurement values, timestamp values, and sensor identifiers, and updating an in-memory data store. This cycle continues until a specified output update time is reached, at which point the stored data is processed and enriched using defined windows. Another notable patent is "Automated streaming data model generation," which details a computing device that automatically generates an ESP model to process events. This model includes a mapping dataset created from configuration and device information, allowing for efficient measurement processing.
Career Highlights
Cavalier is currently employed at SAS Institute Inc., a leading analytics software company. His role involves developing innovative solutions that leverage data processing technologies to improve business intelligence and analytics capabilities.
Collaborations
Cavalier has collaborated with notable colleagues such as Steven William Enck and Sarah Jeanette Gauby. Their combined expertise contributes to the advancement of technologies in data processing and analytics.
Conclusion
Charles Michael Cavalier's contributions to the field of event stream processing demonstrate his innovative spirit and commitment to enhancing data management systems. His patents reflect a deep understanding of computational processes and a drive to automate and improve efficiency in data handling.