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Exploratory Data Analysis (EDA) of Global Food Wastage Data

The dashboard provides an Exploratory Data Analysis (EDA) of Global Food Wastage Data, showcasing key metrics, visualizations, and filters to analyze food waste trends across different categories, regions, and years.

EDA Dashboard in Power BI on Global Food Wastage Data

Get the dataset on kaggle : https://www.kaggle.com/datasets/atharvasoundankar/global-food-wastage-dataset-2018-2024

Key Sections:

  1. Top Metrics:
    • Avg of Avg Waste Per Capita: 109.46 (average food waste per person).
    • Economic Loss: 125.20M (total financial loss due to food waste).
    • Population: 3.53M (considered population size).
    • Total Waste (Tons): 125.31M (total quantity of food waste globally).
  2. Food Waste Breakdown by Category:
    • A donut chart shows the distribution of total food waste (in tons) by different food categories such as:
      • Prepared Food (14.31%)
      • Beverages (13.05%)
      • Bakery Items (12.01%)
      • Frozen Food (12.27%)
      • Fruits & Vegetables (12.44%)
      • Meat & Seafood
      • Dairy Products
  3. Geographical Impact (Map Visualization):
    • Displays the sum of economic loss and total waste (tons) by country.
    • Darker shades indicate higher economic losses due to food wastage.
  4. Population vs. Household Waste by Food Category:
    • A bar chart compares the population (million) and household waste (%) per food category.
    • Example: Prepared food waste is the highest, while grains & cereals have relatively lower waste.
  5. Economic Loss vs. Total Waste Correlation (Scatter Plot):
    • A trendline indicates a positive correlation between food waste (tons) and economic loss (million dollars).
    • The more food wasted, the higher the financial loss.

Filters:

  • Food Category: Allows selection of specific food types (Bakery, Beverages, Frozen Food, etc.).
  • Country: Filters data by specific regions.
  • Year: Allows comparison between different years (2018 & 2024).

Conclusion:

This Power BI dashboard provides insights into food waste trends, economic impact, and regional disparities. It helps in identifying key focus areas for reducing food waste and economic losses globally.