Building a BI App – Udemy Course Performance Analysis

Overview

This project focuses on building an end-to-end Business Intelligence application in Power BI using the Udemy Online Education Courses dataset. The objective was to analyse course engagement and performance metrics to identify which courses may require improvement and why.

The project involved data preparation, data modelling, DAX measure creation, dashboard development, and publishing the final report to Power BI Service.

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Objectives

• Analyse course engagement using subscriber and review metrics
• Identify underperforming courses requiring improvement
• Build an interactive Power BI dashboard for stakeholder analysis
• Create KPI-driven insights using DAX measures
• Publish the report to Power BI Service

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Tools & Technologies

• Power BI
• Power Query
• DAX (Data Analysis Expressions)
• Power BI Service
• Data Modelling
• Data Visualisation

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Dataset

Udemy Online Education Courses Dataset

Dataset includes:

• Course ID
• Course Title
• URL
• Paid
• Price ($)
• No. of subscribers
• No. of reviews
• No. of lectures
• Level
• Content Duration (Hours)
• Published Timestamp
• Subject

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Key Steps

1. Data Preparation

• Imported dataset into Power BI
• Cleaned and transformed data using Power Query
• Verified data types and formatting
• Structured data for analysis and reporting

2. Data Modelling

Created calculated columns for enhanced business analysis and segmentation:

Price Category =
SWITCH(
    TRUE(),
    Courses[Price ($)] = 0, "Free",
    Courses[Price ($)] <= 50, "Low Cost",
    Courses[Price ($)] <= 100, "Mid Range",
    "Premium"
)

Duration Category =
SWITCH(
    TRUE(),
    Courses[Content Duration (Hours)] < 2, "Short",
    Courses[Content Duration (Hours)] < 10, "Medium",
    "Long"
)

Popularity Category =
SWITCH(
    TRUE(),
    Courses[No. of subscribers] < 1000, "Low",
    Courses[No. of subscribers] < 10000, "Moderate",
    "High"
)

Engagement Risk =
SWITCH(
    TRUE(),
    Courses[No. of subscribers] > 10000 &&
    Courses[No. of reviews] < 100,
    "High Risk",

    Courses[No. of reviews] > 500,
    "Healthy",

    "Moderate"
)

Estimated Revenue =
Courses[Price ($)] * Courses[No. of subscribers]

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3. DAX Measure Creation

Key KPI measures included:

Total Courses = DISTINCTCOUNT(Courses[Course ID])

Total Subscribers = SUM(Courses[No. of subscribers])

Total Reviews = SUM(Courses[No. of reviews])

Average Price = AVERAGE(Courses[Price ($)])

Average Duration = AVERAGE(Courses[Content Duration (Hours)])

Review Rate =
DIVIDE(
    [Total Reviews],
    [Total Subscribers]
)

Avg Subscribers per Course =
DIVIDE(
    [Total Subscribers],
    [Total Courses]
)

Total Revenue = SUM(Courses[Estimated Revenue])

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Dashboard Features

KPI Cards

• Total Courses
• Total Subscribers
• Estimated Revenue Potential
• Review Rate

Visualisations

• Subscriber analysis by subject
• Review rate analysis by duration category
• Scatter plot for course engagement analysis
• Course publishing trends over time

Interactive Features

• Subject slicers
• Level filters
• Price category filters
• Duration category filters
• Popularity segmentation

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Key Insights

• Web Development courses generated the highest subscriber engagement across the platform
• Longer-duration courses achieved stronger review rates than shorter courses
• Several highly subscribed courses demonstrated relatively low engagement metrics
• Beginner-level courses showed stronger participation trends compared to advanced-level content

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Business Value

• Demonstrates end-to-end BI workflow development using Power BI
• Supports data-driven decision-making for course improvement prioritisation
• Highlights the importance of engagement analysis within online learning platforms
• Showcases practical dashboard design, KPI reporting, and analytical storytelling skills

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Challenges Faced

• Designing meaningful calculated categories for analysis
• Building effective DAX measures for KPI reporting
• Managing scatter plot aggregation and visual clarity
• Balancing dashboard readability with analytical depth

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Outcome

Successfully developed and published an interactive Power BI report analysing course engagement patterns using subscribers, reviews, duration, and pricing metrics. The project demonstrates practical skills in Power BI, DAX, data modelling, and business intelligence reporting.

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Dashboard Preview

Screenshots will be in the 'screenshots' folder.

Report Access

Published to Power BI Service via My Workspace. Link is found here - (https://app.powerbi.com/groups/me/reports/b1b8bee7-26f6-40a2-9a1e-cf5c27b25df6/3e650dcd31584a7e7060?experience=power-bi)

Future Improvements

• Implement Row-Level Security (RLS)
• Expand KPI analysis with additional learner engagement metrics
• Create advanced time intelligence measures
• Enhance dashboard interactivity and drill-through functionality