Student Performance & Demographic Correlation Analytics

Category: Academic Data Research & UX Design Tools Used: Power BI Desktop, Power Query, Data Modeling, Kaggle Open Dataset Project Scope: Exploring the socio-economic and demographic drivers of academic success.

Data Import & Modeling Phase

Data Acquisition

The foundation of this project is a specialized dataset from Kaggle containing standardized test scores in Math, Reading, and Writing, alongside multi-dimensional demographic variables.

Data Transformation (ETL)

Using Power Query, I prepared the raw data for high-level analysis:

• Categorical Grouping: I standardized and categorized Parental Education Levels (e.g., Associate's Degree, Master's Degree) to create a clean hierarchy for filtering.
• Feature Optimization: Renamed and reformatted Study Groups and Test Preparation status to ensure they functioned as intuitive categorical filters.
• DataType Alignment: Verified all test scores were formatted as whole numbers to allow for accurate mathematical averaging across different demographic segments.

2. Multi-Perspective Analysis

I designed this dashboard to move beyond simple score tracking and instead focus on Correlation—understanding which factors outside the classroom impact performance inside the classroom.

Demographics

• Purpose: To visualize the distribution of the student body based on parental education levels.
• Insight: This allows administrators to quickly identify the largest socio-economic cohorts within the school and understand the background of their student population at a glance.

Cross-Subject Correlation Charts