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Building a COVID-19 Dashboard with Tableau Building a COVID-19 Dashboard with Tableau
We all are experts in telling stories with words and sentences. But, have you ever heard of telling stories with data? This sounds intriguing.... Building a COVID-19 Dashboard with Tableau

We all are experts in telling stories with words and sentences. But, have you ever heard of telling stories with data? This sounds intriguing. Well, it sounded the same for me too.  Being able to tell stories with data is a skill that is becoming ever more important in our world of increasing data and desire for data-driven decision making. That is where it takes you- the analyst or communicator of the information- to bring that story visually and contextually to life. And if you are thinking about the tools- I have that answer ready for you. In this article, I will explain my journey of how I visualized the COVID-19 data with a powerful visualization tool using some of the best practices that I followed throughout the process. 

[Related article: Data Visualization and Dashboards in the Era of Covid-19]

Which tool do I use?

Recently, I have been working on building my data visualization skills and I chose Tableau as a tool for telling stories with data. Tableau is one of the powerful data visualization tools and it is also used in business intelligence, marketing, and more fields. It is used not only for visualizing the data but also for hypothesis testing, feature engineering, dash-boarding, and storytelling, which are very important parts of a data science project. The great thing about Tableau software is that it does not require any technical or any kind of programming skills to operate. The tool has garnered interest among the people from all sectors such as business, researchers, different industries, etc. There are many BI tools available in the market and you can use them as per your requirements, but Tableau covers all the aspects of creating visuals and gives you the freedom to convey information to others in your own way. 

https://odsc.com/europe/

Building a COVID-19 Dashboard:

One of the best examples of effective and interactive dashboards could be the recent COVID-19 dashboards. It is the basis of how we are seeing and measuring the impact of this virus in the world. Various countries and even states or regions have created their own COVID-19 dashboards to make people aware of the pandemic and asking them to take preventive measures. This is a great example of using data to educate the masses based on finding insights and educate them through visuals. 

Many organizations including John Hopkins, Center for Disease Control and Prevention (CDC), as well as The New York Times (which is aggregating data from state and local governments and health departments for the United States), are providing a global coronavirus tracker to help you stay updated on the confirmed case and death totals, the spread of coronavirus, and the places most impacted by this pandemic. You can also download the dataset from the CDC website or the New York Times GitHub to access the data.

I took the U.S. County-Level Data from the GitHub repository of The New York Times. The data is in .csv format and has the daily number of cases nationwide, on the state level and county level as well. It is a great dataset for you as well to get started with creating an amazing dashboard. When I saw the data, I asked myself some questions: What do I want to show with this data? What takeaways do I want my audience to grab? How can I make it visually appealing? Let see them one by one.

covid 19 tableau
My main aim is to focus the audience’s attention on the number of cases, and details based on the different states and the county-wise details of each state based upon the user’s interest. The data can tell which states have the most and least number of cases, deaths, and how well the condition is by calculating the mortality rate as well. There are two dashboards here: the first one is the entire view of the United States where you can see the total number of cases and deaths overall U.S. and the current mortality rate. On the right side of the dashboard, you can see the top 5 states with the highest number of cases and 5 states with the least mortality rate. 

covid 19 tableau

When you click on the red state bubble which represents the number of cases, you come to the second dashboard where you see the state-wise details showing you the number of cases in that state, the deaths, and mortality rate. You see the state map highlighted with the county which is worst hit by COVID-19. On the left side, you can see how the cases and deaths went increasing day by day. And the county wise report is generated on the right side of the dashboard. I have specifically used the blue color to show the number of cases and red color to show the number of deaths. 

When you want to go back to the primary dashboard, you have a back button to “Go back to Primary Dashboard.” Now you can see the overall U.S. dashboard and click on another state to get the granular details again. This is the working of my COVID-19 dashboard. Here is a link to the dashboard.

You can play with the dashboard and I would love to hear your feedback or suggestions on this one.

If you want to learn data visualization, join me at the ODSC Europe Conference where you learn from the industry experts about the best practices of data visualization and learn how to do it efficiently at scale. I personally learned a lot from the data visualization workshops at the Virtual East ODSC Conferences where I had a chance to learn from experts Zona Kostic and Diedre Downing about the power of visualization and how you can become a data-visualization rockstar. You can also attend the upcoming conferences by using the promo code ‘AAFAZ’ to save 50% on the tickets. For learning Tableau, you can access the free e-learning resources on the official website and start creating great visuals. I would also recommend you all to read the book “Storytelling with Data” by Cole Knaflic. She has used simple examples and explains how to communicate to audiences in an effective way.  

Do give a thumbs-up if you like this article and share it with your connections who are new to the data science field and can get help with this article. Connect with me on LinkedIn for any discussion, queries, or suggestions.

This was a guest article by ODSC Brand Ambassador Aafaz Ilahi.

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The Open Data Science community is passionate and diverse, and we always welcome contributions from data science professionals! All of the articles under this profile are from our community, with individual authors mentioned in the text itself.

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