Data is an asset to fight the spread of COVID-19. Data scientists and analysts use COVID-19 data to inform decisions that save lives. But the United States has struggled with managing the new high volumes of data from 6,000 hospitals and 50 states. The CDC has an aging system, and the Health and Human Services Agency, who’s responsible for this data, is not really addressing some of the core problems. 

Paul Balas embarked on a project to assess the state of COVID-19 data. He will share his work and his findings in this session. Join us and you will learn about:

  • The technology and processes behind the US government’s COVID-19 data
  • Key issues that hindered the use of that data, including data quality and system agility
  • Natural language processing and semantic analysis used in this study
  • Automating key data engineering processes to speed up analytics projects delivery
  • A roadmap for solving systemic issues in building an agile data analytics foundation

Register for Webinar Recording and Slides


Paul Balas, 303 Computing
Kamal Maheshwari,