Marietta, GA, United States of America

John A Old



Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2016

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1 patent (USPTO):Explore Patents

Title: John A. Old: Innovator in Advanced Analytics

Introduction

John A. Old is a notable inventor based in Marietta, GA, who has made significant contributions to the field of advanced analytics. With a focus on improving data processing for predictive modeling, his work has the potential to enhance decision-making across various industries.

Latest Patents

John A. Old holds a patent titled "Flexible time-based aggregated derivations for advanced analytics." This patent encompasses methods, systems, and devices designed to improve pre-modeling processing of data for predictive modeling. The computing device described in the patent is configured to perform operations for processing client data using metadata that outlines various client-specific parameters. The device can load client data into stage tables based on these parameters, such as flat file locations. It also conducts validation checks on the loaded data to identify duplication records and deleted records. Additionally, the device can generate weekly aggregated tables based on custom aggregation timeframes and archive aggregated data for future use.

Career Highlights

John A. Old is currently employed at Omnitracs, LLC, where he applies his expertise in data analytics and predictive modeling. His innovative approach to data processing has positioned him as a valuable asset in his field.

Collaborations

Throughout his career, John has collaborated with talented individuals such as Patrick M. Ritto and Pratyush Verma. These collaborations have further enriched his work and contributed to advancements in analytics.

Conclusion

John A. Old's contributions to advanced analytics through his patent and work at Omnitracs, LLC, highlight his role as an influential inventor in the field. His innovative methods for data processing are paving the way for improved predictive modeling and analytics.

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