Power BI Dashboard on  COVID-19 Data

Project Objective

To develop an interactive Power BI dashboard using live web data to monitor global COVID-19 trends and support data-driven decisions for public health policy.

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Dataset Description (Fetched from the Web URL)

The dataset from Worldometers contains the following columns:

Column Name	Description
Country, Other	Country name
Total Cases	Cumulative COVID-19 confirmed cases
Total Deaths	Cumulative deaths caused by COVID-19
Total Recovered	Cumulative recovered patients
Tot Cases/1M pop	Cases per million population
Deaths/1M pop	Deaths per million population
Population	Country’s population

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Step-by-Step Process to Connect and Transform the Data

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Step 1: Connect Web Data to Power BI

1. Open Power BI Desktop.

2. Go to Home > Get Data > Web.

3. Paste the URL:

   https://www.worldometers.info/coronavirus/
   

4. Click OK.

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Step 2: Navigate the Web Table

1. Power BI will load all the tables available on the webpage.

2. Look for the table that lists countries and COVID-19 stats (usually named Table 0 or similar).

3. Preview the table and click Load (or Transform Data if cleansing is needed).

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Step 3: Clean and Transform Data in Power Query

• Click Transform Data.

• Apply the following transformations:

Task	Action
Remove unnecessary rows	Filter out rows where "Country" is null or blank.
Rename columns	Clean the column names (remove newline characters and special characters).
Change data types	Convert number columns (e.g., Total Cases, Deaths) from Text to Whole Number.
Remove commas and plus signs	Use Replace Values: remove commas , and +.
Trim whitespace	Select all columns > Transform > Format > Trim.
Sort Data	Sort by Total Cases or Deaths for ranking.
Add Index	Optional: Add an index column to represent ranks.

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Step 4: Load Cleaned Data to Power BI Model

• After cleaning, click Close & Apply.

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Step 5: Build Visualizations

Use these chart types:

• Map Visual: Show country-wise spread.

• Bar/Column Chart: Compare top 10 countries by Total Cases, Deaths, Recovered.

• Card Visuals: Show global KPIs (Total Cases, Deaths, Recovered).

• Line Chart (Optional): If time series data is added later.

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Research Questions for Analysis

These questions can form the core analysis tasks for the dashboard:

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RQ1: Which countries have the highest number of COVID-19 cases and deaths?

• Visualization: Bar chart sorted by Total Cases or Total Deaths.

• Insights: Identify the top 10 affected countries.

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RQ2: What is the COVID-19 death rate per million population across countries?

• Visualization: Bar chart with Deaths/1M pop.

• Insights: Helps normalize data by population size.

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RQ3: Which countries have the highest recovery rate?

• Measure: Recovery Rate = Total Recovered / Total Cases

• Visualization: Sorted bar chart by Recovery Rate.

• Insights: Identifies efficiency of healthcare systems.

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RQ4: What is the global case fatality rate (CFR)?

• Measure: CFR = Total Deaths / Total Cases

• KPI card or DAX measure.

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RQ5: How does COVID-19 impact countries relative to their population size?

• Use Tot Cases/1M pop and Deaths/1M pop.

• Combine with map visuals for comparative impact.

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KPIs to Highlight in Dashboard

• Total Global Cases

• Total Global Deaths

• Total Recovered

• Case Fatality Rate (CFR)

• Country with highest infections

• Country with highest deaths per million