The coronavirus (COVID-19) outbreaks have been dominating global news headlines for the last several weeks. There are new cases being reported every day about the number of infections and even new methodologies for counting the suspected and confirmed infections.
Working at an embedded analytics company, I naturally thought about the importance of data and the analysis being done by experts in the medical field to help contain the spread of the outbreak—more specifically, the importance of tracking data, having access to recent and accurate data, and making sure that data can be clearly communicated and easily interpreted. The ability to visualize rapidly changing data for analysis during a public health emergency is critical to the strategy for stemming the outbreak.
Visualizing the Data
I wanted to see what type of information was publicly available on the internet about COVID-19. After a quick search, I stumbled across data from the National Institutes of Health (NIH). It includes information on reported infections by country and source isolation. Using Zoomdata from Logi Analytics, I was able to create a dashboard with visuals that organized and analyzed the data by:
- Population of reported cases by country
- Ranking of countries with infected cases
- Number of cases and detection method
- A timeline and number of reported cases
- Global map view of countries with reported infections
Within 45 minutes, I created a dashboard that provided a comprehensive and easily consumable view of the coronavirus data in multiple chart and graphic analyses. The ease of use and agility of a dashboard is especially useful to support time-sensitive analysis and rapidly changing datasets. During a global health epidemic, the option to forego wait times typically required of a complex deployment of data analytics is not only beneficial but crucial in disseminating actionable information that can enable governments, agencies, and medical facilities and experts to minimize and stem the spread of an outbreak.
Benefits for Application Teams
Application teams are often faced with the challenge of creating visualizations from newly introduced datasets or data sources, and embedding dashboards directly into their core applications rapidly. While embedding analytics makes the host application more valuable, the challenge becomes more complex when working with dynamic data sources such as real-time data streams—dashboards need to render the data immediately and with a high degree of granularity.
The ability to minimize the development and authoring effort, and fast-tracking the time to production of analytics has significant advantages in time-critical scenarios such as a global health crisis. This key capability can also be leveraged to quickly respond and deliver on customers’ new and evolving analytics requirements, which is a much more common problem that application teams face today as organizations increasingly seek ways to gain more immediate and actionable insights from their data.