From the course: Using Public Health Dashboards

Overview of dashboards

From the course: Using Public Health Dashboards

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Overview of dashboards

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- [Instructor] Since the cases of novel coronavirus were first reported in China in December of 2019, we've seen it spread across the world and become a worldwide phenomenon. Historically, government agencies have used statistics as a way to report to the public the impact of a pandemic or any other epidemic that is happening. Nowadays, because of technology's advancement, we can now have other sources of gathering information, as well as providing information to the public. One great tool for being able to provide information to the public are dashboards. In addition to new publications and articles that are being released daily by journalists and reporters, there's also numerous dashboards and sources that are available out there to be able to get more information about COVID-19. Dashboards have become one of the most popular sources of information in part because it provides a interactive way of gaining insight into coronavirus. It can also be automatically updated and viewed in real time or relative real time. The global nature of COVID-19 has led to a global effort in collecting information about the pandemic. While the COVID-19 data set is robust, it still has a lot of missing information and other such issues that need to be taken into account. It is far from perfect, nor is it in a state where we can assume that everything is accurate. However, because of the global effort, there is at least information and data being collected regularly and improvements to how we're processing the information that is happening every day. But, of course, just to see a visualization isn't enough. We have to also understand what the visualizations and the dashboard is showing us. That means understanding metrics and calculations as well as where the data comes from and how it's being processed. For anyone who's a novice or are relative new to the field, understanding dashboards can help you gain understanding into the data in a way that's more palatable because it gives you a technology to interact with rather than having to look at code or the data itself.

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