Interactive Power BI dashboard analyzing EdTech financial performance (FY23–FY24) | Python (Pandas) generated dataset | KPI Cards, H1/H2 Slicers, Revenue trend, Net Income & Subscriber analytics
This project presents a corporate-grade, interactive financial analytics dashboard built in Power BI, powered by a Python-generated dataset (Pandas + NumPy). It simulates a real-world EdTech business intelligence use case — tracking 2 years of financial and subscriber performance for strategic decision-making by senior management.
Business Question: How has the EdTech company's revenue, profitability, and subscriber base trended across FY2023–FY2024, and where does management need to act?
| Metric | FY23–FY24 Value | Trend |
|---|---|---|
| Total Revenue | $1,336.50 Million | 📉 Declining QoQ |
| Net Income | -$362.60 Million | 🔴 Deep Losses in H2 FY24 |
| Active Subscribers | 35.70 Million (cumulative) | 📉 Dropped to 3.8M by Q3 FY24 |
| Worst Quarter | 2024 Q3 | Net Loss of -$212.6M |
| Best Quarter | 2023 Q2 | Only profitable quarter (+$24.6M) |
Based on the dashboard analysis, the following strategic actions are recommended:
-
SUBSCRIBER RETENTION IS CRITICAL Active subscribers dropped from 5.1M (Q1 FY23) to 3.8M (Q3 FY24) — a 25% decline. The company must investigate churn reasons and invest in retention programs before acquiring new users.
-
H2 PERFORMANCE IS CONSISTENTLY WEAK Both FY23 and FY24 show revenue dips in H2 (Q3 specifically). This suggests a seasonal pattern. Management should plan targeted marketing campaigns and product launches in Q3 to counter this trend.
-
SUBSCRIPTION REVENUE DEPENDENCY IS A RISK ~89% of total revenue comes from subscriptions. Any churn spike directly threatens the business. Diversifying into corporate training, certifications, or B2B partnerships is recommended.
-
COST RESTRUCTURING IS URGENT Q3 FY24 net loss of -$212.6M is a critical red flag. Revenue declined only moderately, but losses spiked sharply — indicating operating costs are growing faster than revenue. An immediate cost audit is needed.
| Tool | Purpose |
|---|---|
| Python (Pandas) | Dataset generation & QoQ growth calculation |
| Jupyter Notebook | Exploratory data wrangling & CSV export |
| Power BI Desktop | Interactive dashboard design & DAX measures |
Edtech-Financial-Analytics/
│
├── data/
│ └── business_problem.docx # Business Questions
│ └── Edtech_Financial_Earnings_23_24.csv # Python-generated financial dataset
│
├── notebooks/
│ └── data_generation.ipynb # Jupyter Notebook for dataset creation
│
├── dashboard/
│ └── EdTech_Financial_Earnings_23_24_Dashboard.pbix # Power BI dashboard file
│
├── assets/
│ └── logo_transparent.png # EdTech logo (transparent background)
│
├── dashboard_preview.png # Dashboard screenshot for README
└── README.md
# Install dependencies
pip install pandas numpy
# Run the notebook or script
jupyter notebook notebooks/data_generation.ipynb- Install Power BI Desktop (free)
- Open
dashboard/EdTech_Financial_Earnings_23_24_Dashboard.pbix - If prompted, re-link the data source to
data/EdTech_Financial_Earnings_23_24.csv
- Realistic mock dataset generated from public EdTech earnings reports (FY23–FY24)
- QoQ Revenue Growth % calculated using
pct_change()in Pandas - Clean CSV export ready for BI tool consumption
- 3 KPI Cards with custom formatting:
- Revenue:
Display Units → Noneto show exact millions - Net Income: Accounting-style negative format with brackets
($362.60M) - Subscribers: Aggregation changed from
Sum → Averageto reflect true active base
- Revenue:
- Interactive Slicers: H1/H2 Half-Year buttons + Quarter Period dropdown
- Advanced Chart Techniques:
- Dual-line chart for Revenue vs. Subscription Revenue trend
- Area chart with 0% shade transparency for solid subscriber base visualization
- Bar chart with Zoom Slider enabled to handle extreme outlier (-$212.6M in Q3 FY24) without distorting chart scale
- UI/UX Polish:
- Rounded corners (10px) + drop shadows for 3D "card pop-out" effect
- Transparent PNG logo placed on Dark Navy branded header
- Layer management via Selection Pane (Send to Back/Bring Forward)
- Zero padding on cards for pixel-perfect alignment
| Column | Type | Description |
|---|---|---|
Year |
int | Fiscal Year (2023 / 2024) |
Quarter |
str | Q1, Q2, Q3, Q4 |
Half_Year |
str | H1 or H2 |
Total_Revenue_Millions |
float | Total quarterly revenue ($M) |
Subscription_Revenue_Millions |
float | Subscription-only revenue ($M) |
Net_Income_Loss_Millions |
float | Net profit or loss ($M) |
Subscribers_Millions |
float | Active subscriber base (M) |
QoQ_Revenue_Growth_% |
float | Quarter-over-Quarter revenue growth % |
- ✅ Data Engineering: Python-based synthetic dataset generation using Pandas
- ✅ Business Intelligence: Power BI dashboard design with corporate branding
- ✅ DAX & Aggregation Logic: Correct metric aggregation (Sum vs Average use cases)
- ✅ Data Storytelling: Translating raw financials into executive-level visual narrative
- ✅ UI/UX Design: Corporate theming, layering, slicers, and 3D card effects
- ✅ Outlier Handling: Zoom Slider technique for skewed financial data
This dashboard was built as part of a portfolio project to demonstrate real-world Business Intelligence and Data Analytics skills applicable to Data Analyst roles in EdTech, FinTech, and SaaS domains.
Girish Pathak
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