Coopersburg, PA, United States of America

Isaac Rieksts

This inventor holds 1 USPTO granted patent. Top assignee: Health Market Science. Active years: 2014.


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 7(Granted Patents)


Company Filing History:


Years Active: 2014

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1 patent (USPTO):Explore Patents

Title: Isaac Rieksts: Innovator in Master Data Management

Introduction

Isaac Rieksts is a notable inventor based in Coopersburg, PA (US). He has made significant contributions to the field of computer-implemented methods, particularly in master data management. His innovative approach leverages non-relational databases to dynamically aggregate data of distinct formats and content.

Latest Patents

Isaac Rieksts holds a patent for "Computer-implemented methods and computer systems for master data management leveraging a non-relational databases for dynamically aggregating data of distinct formats and/or content." This invention outlines a method that includes receiving data feeds associated with healthcare-related entities, where the data schema is unknown prior to receipt. The method automatically determines, in real-time, various data fragments and stores the entity information across distributed non-relational computer databases. This process creates verified records of entities at specific times, enhancing the efficiency of data management in healthcare.

Career Highlights

Isaac Rieksts is currently employed at Health Market Science, where he applies his expertise in data management. His work focuses on improving the ways healthcare data is aggregated and utilized, making significant strides in the industry.

Collaborations

Isaac collaborates with talented professionals such as Brian O'Neill and Shantha Andrews. Their combined efforts contribute to the advancement of innovative solutions in the field of healthcare data management.

Conclusion

Isaac Rieksts is a pioneering inventor whose work in master data management is shaping the future of healthcare data utilization. His contributions are vital in enhancing the efficiency and effectiveness of data management systems.

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