New Delhi, India

Sumanta Kumar Bhowmik


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2014

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2 patents (USPTO):Explore Patents

Title: Innovations by Sumanta Kumar Bhowmik

Introduction

Sumanta Kumar Bhowmik is a notable inventor based in New Delhi, India. He has made significant contributions to the field of data processing, particularly in the area of streaming data analytics. With a total of 2 patents to his name, Bhowmik's work is recognized for its innovative approach to handling large volumes of data.

Latest Patents

Bhowmik's latest patents focus on the distributed processing of streaming data records. The representative embodiments of his method facilitate interactive analytics by receiving data records at multiple distributed computational nodes. The process involves establishing and storing dimensions corresponding to the attributes of the data records. It also includes parsing the streaming data records to identify matches to at least one of the dimensions. Based on this, the method reduces the number of data records to create a targeted subset. The targeted subsets are then re-distributed among the computational nodes according to the stored dimensions. Additionally, a database is updated to store measures of the dimensions in accordance with the targeted subsets, allowing for efficient responses to queries based on these measures.

Career Highlights

Sumanta Kumar Bhowmik is currently employed at Guavus, Inc., where he continues to innovate in the field of data analytics. His work has been instrumental in advancing the capabilities of distributed processing systems.

Collaborations

Bhowmik collaborates with talented professionals such as Jaskaran Singh Bawa and Bijay Singh Bisht, contributing to a dynamic work environment that fosters innovation.

Conclusion

Sumanta Kumar Bhowmik's contributions to the field of data processing through his patents demonstrate his commitment to advancing technology. His innovative methods for handling streaming data are paving the way for more efficient data analytics solutions.

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