Comprehensive global analysis of university success utilizing Power BI, Excel, and SQL integrating data from diverse ranking systems and criteria.
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Link to Access the PowerPoint Presentation and Video Walkthrough
- Access the PowerPoint presentation for an in-depth understanding of the project. Additionally, watch the accompanying video walkthrough for a detailed explanation of key insights and methodologies.
The "University Success Analysis" is a comprehensive capstone project exploring the impact of ranking systems on universities. It aims to compare university rankings, evaluate the influence of ranking criteria, and analyze dynamic shifts in university metrics over time.
This project holds significant implications for gaining insights into and enhancing the performance of universities. The structured dataset, combined with MECE analysis and Power BI visualizations, enables a comprehensive understanding of the factors influencing university success.
- File Name: MECE_Breakdown.docx
- Description: Uncover the logic behind the process! This guide provides a closer look at how datasets are systematically analyzed using the MECE (Mutually Exclusive, Collectively Exhaustive) method.
The MECE diagram outlines the structured approach applied in dissecting and evaluating the dataset. This method ensures that every component is distinct (Mutually Exclusive) while covering all possibilities (Collectively Exhaustive). It serves as the foundation for uncovering valuable insights and patterns across various dimensions, contributing to a comprehensive understanding of the data.
- File Name: University_Success_Analysis_EDA.xlsx
- Description: Conduct a thorough Exploratory Data Analysis (EDA) using SQL and Excel. This file includes data aggregation, visualizations, and insightful screenshots for a comprehensive understanding.
- File Name: PowerBI_University_Success_Analysis.pbix
- Description: Harness the capabilities of Power BI! This file addresses problem statements, visualizes data, and constructs dashboards for a comprehensive view of university rankings.
The Entity-Relationship (ER) Diagram illustrates interconnected data entities, providing a visual guide to relationships between countries, universities, ranking systems, criteria, and their dynamic interactions in global higher education.
- File Name: Project_Presentation.pptx
- Description: Commence a visual journey! This PowerPoint presentation provides an overview of the project, methodologies, and a detailed breakdown of each problem statement addressed during the exploratory data analysis (EDA) and Power BI phases.
- Link to Access the PowerPoint Presentation and Video Walkthrough
Access the PowerPoint presentation for a comprehensive overview of the project, and watch the accompanying video walkthrough for detailed insights and methodologies
- File Name: University_Success_Detailed_Analysis_Report.docx
- Description: Explore the details! This comprehensive document guides you through every stage of the project, from data gathering and transformation to systematic breakdown, integration of tools, insights gained through exploratory data analysis (EDA), and implementation of solutions using Power BI.
The dataset offers comprehensive insights into universities, their rankings, and associated metrics. Structured with key tables, it enables a detailed analysis, supporting informed decision-making in higher education.
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Country:
- Unique IDs and names of countries.
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University:
- Unique IDs, country IDs, and names of universities.
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Ranking System:
- Unique IDs and names of ranking systems.
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Ranking Criteria:
- Unique IDs, ranking system IDs, and names of criteria.
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University Year:
- University IDs, years, student metrics, and international student percentages.
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University Ranking Year:
- University IDs, ranking criteria IDs, years, and scores.
- Evaluate and Compare University Rankings.
- Identify Key Factors Affecting Rankings.
- Conduct Regional Analysis.
- Explore Long-term Trends.
- Perform Correlation Analysis.
- Create Data Visualizations and Reports.
- Implement Predictive Modeling.
Explore key insights derived from the Exploratory Data Analysis (EDA) and Power BI phases, including:
- Regional Patterns
- Impact of Criteria
- Temporal Changes
- Correlation Analysis
Developed four detailed Power BI dashboards to provide a clear and thorough visual representation of university rankings.
- Visualizes ranking trends and metrics based on countries.
- Offers insights into individual university performance and metrics.
- Compares and contrasts rankings across different systems.
- Examines temporal changes in university metrics and rankings.
Seamlessly navigate the project with these simple steps:
- Launch Power BI Desktop:
- Open Power BI Desktop.
- Explore and open the
PowerBI_University_Success_Analysis.pbixfile.
- Explore Data with Excel:
- Use Microsoft Excel for in-depth analysis.
- Open
EDA_University_Success_Analysis.xlsxto visualize and explore data.
- Detailed Project Overview:
- Gain profound insights and methodologies.
- Access
University_Success_Detailed_Analysis_Report.docxfor a deep understanding of the project lifecycle, covering data collection, transformation, MECE breakdown, tool integration, EDA insights, and Power BI solutions.
Your feedback is invaluable! If you have suggestions, or questions, or would like to contribute to the "University Success Analysis" project, feel free to:
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Open an Issue:
- For bug reports or feature requests, open an issue.
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Submit a Pull Request:
- Contribute enhancements or fixes by submitting a pull request.
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Reach Out:
- You can reach out via email.
To clone the repository and access the project files locally, use the following command:
git clone https://github.com/virajbhutada/Global-Universities-Success-Analysis.gitYour active engagement enhances the quality of this project, and your valuable insights are truly appreciated! Your contributions contribute to the excellence of the "University Success Analysis."
Explore, Analyze, and Contribute! 🌐📊