Jon Falker
Data Enrichment
Data Operations
Expert Interview
Redica Systems
Expert Interview: The Role of Data Operations Inside Quality and Regulatory Intelligence
Published on
October 11, 2023
Category
Written by

Expert Interview: The Role of Data Operations Inside Quality and Regulatory Intelligence

Expert Interview: The Role of Data Operations Inside Quality and Regulatory Intelligence

Expert Interview: The Role of Data Operations Inside Quality and Regulatory Intelligence

Published on
October 11, 2023
Category
Written by

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Regular posts covering guidance changes, inspection findings, data methodology, and Redica product updates.

Data Operations is a fairly new discipline, but it has rapidly become critical to the success of nearly every type of company. In a September 2023 interview with Scott Sherrill, the Vice President of Data Operations at Redica Systems, we discussed the greatest challenges and opportunities for DataOps within the Quality and Regulatory Intelligence space, as well as what the future might hold.

The video chapters and accompanying timestamps are here for your easy reference:

  • 0:00 – Introduction
  • 0:35 – Scott’s Role at Redica Systems
  • 1:37 – Scott’s Background and Experience
  • 5:06 – The Importance of Data Operations and Data Science
  • 10:00 – Intelligent Document Processing (IDP)
  • 13:52 – Analyzing and Enriching Data with IDP
  • 16:14 – Benefits of Redica Systems for Life Sciences Companies
  • 18:49 – Future of Transparency and Data Enrichment

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If you’d like to get a demo of Redica Systems Quality and Regulatory Intelligence, get in touch here.

About the Speaker

Scott Circle

Scott Sherrill is Redica Systems’ VP of Data and AI Operations, where he leads the team responsible for acquiring, extracting, labelling, and analyzing Redica’s worldwide inspection and regulatory data. Scott began his career in law before transferring to the business side in a private equity company. Prior to Redica, Scott led operations and finance as COO at Aumni, Inc., where he helped to build a 150+ person data operations team to extract and label unstructured data.

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