Data Visualization in a Pandemic World
A data analytics leader examines errors in COVID-19 data analysis and key actions that make a difference in understanding the progression of a global pandemic.
Written by Greg Green, PhD. 7-minute read
- Data Analytics
- Science in Practice
- Technology and Innovation
- The outbreak of COVID-19 saw the rapid development of data structures and visualizations to track infections, hospitalizations, and deaths.
- Inevitably, attempts to quantify the novel disease in such a fast-evolving environment led to erroneous reporting.
- By highlighting three key areas where mistakes are likely, future data analysts will be prepared to take action sooner and potentially save lives.
At a time when false narratives spread rapidly and undermine traditional sources of authority, the integrity in data science and analytics has become especially critical to building trust and credibility.