{"id":2878,"date":"2023-09-23T18:54:08","date_gmt":"2023-09-23T18:54:08","guid":{"rendered":"https:\/\/www.themindedmarketing.com\/?p=2878"},"modified":"2023-09-23T19:01:43","modified_gmt":"2023-09-23T19:01:43","slug":"covid-in-africa-data-analytics-case-study","status":"publish","type":"post","link":"https:\/\/www.themindedmarketing.com\/covid-in-africa-data-analytics-case-study\/","title":{"rendered":"Covid-19 in Africa: A Data Analytics Case Study (SQL,Tableau)"},"content":{"rendered":"\n

As the world grapples with the devastating impact of the Covid-19 pandemic, one region that has drawn significant attention is Africa. <\/p>\n\n\n\n

As an African myself, I remember how much media coverage was being pushed in continents like Europe, North America, and Asia. <\/p>\n\n\n\n

However, Africa was left far behind and almost forgotten.<\/p>\n\n\n\n

The narrative surrounding the virus’s impact on this vast and diverse continent has been multifaceted, often shrouded in misconceptions and assumptions. <\/p>\n\n\n\n

In this case study, we delve into the trajectory of Covid-19 deaths in Africa. Beyond statistics and headlines, we will uncover how, despite heavy misconceptions about the continent, Africa was actually thriving during the pandemic. <\/p>\n\n\n\n

Join us in exploring the story behind the numbers, as we seek a deeper understanding of Africa’s experience with Covid-19.<\/p>\n\n\n\n

Ask: Finding The Right Questions<\/h2>\n\n\n\n

The main goal of this case study was to clear the misconceptions about the African continent and the impact that the virus was believed to have on it. <\/p>\n\n\n\n

The few news outlets that did talk about African all had one thing to say: Africa is doomed.<\/p>\n\n\n\n

The common belief was that Africa would have some of the world’s highest mortality and infection rates during this period.<\/p>\n\n\n\n

The AA.com<\/a> wrote that the “virus outbreak poses great danger<\/em> to African countries that do not have robust health system.”<\/p>\n\n\n\n

The UN<\/a> put out a brief discussing how “Early estimates were pessimistic regarding the pandemic\u2019s impact on the continent.”<\/p>\n\n\n\n

Reports upon reports of how Africa would not be able to handle the pandemic keep pouring in. <\/p>\n\n\n\n

Until the numbers started to drop.<\/p>\n\n\n\n

From those numbers, we can answer the following question: How much was the actual death toll in Africa compared to other continents?<\/span><\/strong><\/p>\n\n\n\n

Prepare: Prepping the Data<\/h2>\n\n\n\n

In order to get started, it was very important that I find viable, non-biased data. The most trustworthy place to get it from is from WHO (World Health Organization). Thankfully, the data is available for downloading via the WHO Covid 19 Dashboard<\/a>.<\/p>\n\n\n\n

Once the data was downloaded, I had to make a few decisions as to where and how I wanted to store the data.<\/p>\n\n\n\n

I decided to use both BigQuery<\/span><\/strong> and MySQL<\/span><\/strong> for this case.<\/p>\n\n\n\n

Both are very easy to use and can handle millions of rows of data. Which is almost exactly what we got with the data on Covid.<\/p>\n\n\n\n