/FIFA-World-Cup-Data-Analysis

FIFA-World-Cup-Data-Analysis

Power BI Dashboard

You can view my interactive Power BI Report here.

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Project Overview:

This project involves extracting, profiling, and analyzing FIFA World Cup data from the Wikipedia website. The primary focus is on creating a comprehensive report that includes key information such as the year, host country, champion, runner-up, final score, and the number of participating teams. The project aims to provide insightful visualizations for better understanding and interpretation of the data.

Project Steps:

1. Data Extraction:

Extract data from the relevant tables on the Wikipedia page: FIFA World Cup Wikipedia using Power BI import mode.

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2. Data Profiling:

Data Types and Formats:

  • Ed. (Edition):
    Data Type: Numeric
    Description: Represents the edition or number of the FIFA World Cup. It indicates the sequential order of each tournament.

  • Year:
    Data Type: Numeric
    Description: Indicates the calendar year in which the FIFA World Cup tournament took place.

  • Host:
    Data Type: Categorical
    Description: Specifies the country that hosted the FIFA World Cup for a particular edition.

  • Final, Third-place play-off, Champion, Runner-up, Third, Fourth:
    Data Type: Categorical
    Description: These columns provide information about the teams involved in different stages of the tournament:
    "Final" indicates the teams that reached the final match.
    "Third-place play-off" indicates the teams that competed for the third-place position.
    "Champion" indicates the team that won the championship.
    "Runner-up" indicates the team that finished as the runner-up.
    "Third" indicates the team that finished in third place.
    "Fourth" indicates the team that finished in fourth place.

  • No. of teams:
    Data Type: Numeric
    Description: Represents the total number of teams that participated in a specific edition of the FIFA World Cup.

Statistical Summary:

Number of editions of the FIFA World Cup

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Distribution of the World Cup years

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Frequency of hosting by countries

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Frequency of teams winning the championship

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No. of teams image

3. Data Cleaning and ETL:

  • Profile and clean the extracted data.
  • Perform Extract, Transform, and Load (ETL) operations to structure the data for analysis.
  • Load the following fields: Year Host Country Champion Runner-up Final Score Number of Teams

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4. Report Visualization:

I chose appropriate visuals to convey the following insights:
a. Host Country Frequency:
 Display the number of times the championship was hosted by the host country on a map.
b. Top 5 World Cup Winners:
 Highlight the top 5 countries that have won the World Cup the most.
c. Teams Participation:
 Showcase the number of teams that participated in each championship.
d. Detailed Table:
 Create a table displaying all the relevant fields in a clear and organized manner.
e. Yearly Filtering:
 Implement a filter mechanism allowing users to filter the dashboard by year.

This documentation serves as a guide for project execution, ensuring a systematic approach to extracting, processing, and visualizing FIFA World Cup data for meaningful insights.