Summary
I honed my Tableau skills by creating a Covid-19 Vaccination Tracker, delivering insights and marking progress in my data analyst journey. 📈💉
Tools
Tableau
Methods
Dashboard Design, Data Visualization
Functions
Case Sensitive Filter, Charts, Scatter Chart, Trend Line
Project Overview
The Covid Vaccination Tracker project signifies a pivotal moment in my journey as a data analyst. I utilized a guided tutorial by a seasoned data analyst on YouTube to embark on the world of data visualization using Tableau. The project revolves around tracking global Covid-19 vaccination progress.
Learning and Implementation
This project offered me a valuable learning experience by allowing the practical application of Tableau skills through a structured tutorial. Key elements integrated into the dashboard include date filters, country and continent filters, and a dynamic world map. These features empower users to explore vaccination statistics with ease.
Insights Delivered
The project provides answers to critical questions, such as the percentage of the population partially or fully vaccinated against Covid-19, daily vaccine doses administered, distribution of booster doses, and the impact of GDP per capita on vaccination rates. By visualizing these insights, the project serves as a valuable tool for understanding and tracking ongoing global vaccination efforts.
Progress and Growth
While this project was inspired by a YouTube tutorial, it represents a pivotal moment in my progress as a data analyst. It marks the transition from passive learning to active implementation, as I applied the acquired Tableau skills to create an informative dashboard. This journey of turning knowledge into practical results is a fundamental step in my development as a data analyst.
Goals
Learn and apply Tableau skills by following a guided tutorial.
Create an interactive dashboard for tracking global Covid-19 vaccination statistics.
Provide insights on vaccination progress, including population coverage, daily doses, boosters, and socio-economic factors.
Gain hands-on experience in data visualization, transitioning from learning to practical application.
Mark progress and growth in the journey as a data analyst through real-world project implementation.
