Project Context & Problem

Between 2016 and 2022, India’s FinTech ecosystem saw rapid capital deployment exceeding $15 billion. However, data was fragmented, inconsistent, and difficult to interpret. Analysts, early-stage VCs, and founders lacked a centralized, actionable lens to track where capital was flowing, which sectors were efficient, which investors were active, and how repeat behavior shaped market dynamics. Raw datasets were noisy, incomplete, and lacked standardized formats, making trend analysis and strategic decision-making highly challenging. The goal of this project was to build a comprehensive, operator-grade dashboard that could synthesize multi-year funding data, generate actionable insights, and quantify investor and sector-level trends.

Data Acquisition & Cleaning

• Collected 5,047 raw funding records from multiple Kaggle datasets covering startups, funding rounds, and investor details.

• Standardized investor names, city names, and sector tags to ensure consistency across datasets.

• Resolved over 2,200 missing fields manually, including dates, cities, investor roles, and deal-specific information.

• Filtered out non-FinTech entities to maintain dataset relevance.

• Consolidated raw data into 580 high-quality entries ready for analytics and visualization.

Metric Creation & Analysis

• Developed 9 custom metrics using Power BI’s DAX functionality:

  • Capital Velocity: Total Funding / Startup Age

  • Investor Loyalty Score: Repeat Investments / Total Investments

  • Sector Efficiency Index: Average capital per deal per sector

  • Year-on-Year (YoY) growth for deal count and total capital

  • Capital Concentration Ratio for high-impact investors

  • Identification of top-funded sectors and top investors

  • Repeat investor behavior across rounds

  • Startup velocity and growth potential

  • Efficiency of capital allocation across sectors and geographies

• Metrics were designed to deliver actionable insight into investor decision-making, sector performance, and ecosystem health.

Dashboard Design & Visualization

• Built a three-page Power BI dashboard for interactive exploration:

  • Page 1 – Market Overview: Annual capital deployment line chart, deal volume bar chart, YoY growth combo chart, capital concentration donut chart, KPI cards for total capital, average deal size, and peak funding year.

  • Page 2 – Sector & Geography Lens: Treemap of capital allocation by sector, donut chart of sector-wise deal activity, India map showing city-wise capital flow, horizontal bar chart for average ticket size per sector, KPI cards for top-funded and most efficient sectors.

  • Page 3 – Investor Behavior Analysis: Ribbon chart showing investor repeat rate, bar chart of capital deployed by investor, line area chart of capital velocity by startup age, KPI cards for top investors, highest repeat rate, and fastest-growing startups.

• Implemented 4 global slicers (Year, Sector, City, Investor) for quick filtering and actionable insight.

Process & Tools

• Data preprocessing: Python (Pandas) and Jupyter Notebooks for cleaning, merging, and deriving metrics.

• Visualization: Power BI for dashboard creation, DAX metric coding, and chart design.

• Data validation & enrichment: Excel for cross-checking and ensuring dataset integrity.

Insights & Outcomes

• Processed over 3,912 funding rounds into 580 actionable, high-quality entries.

• Tracked 512 unique investors and their repeat behaviors across 61 cities.

• Enabled identification of sector efficiency, investor loyalty, and capital concentration at scale.

• Empowered analysts and early-stage VCs to make data-driven decisions on funding strategy, market trends, and portfolio allocation.

• Highlighted key market patterns:

  • Top-funded sectors and cities for targeted investment.

  • Repeat investor behavior for predictive insights.

  • Growth potential of startups based on capital velocity and funding patterns.

• Delivered an operator-grade tool that combines raw data, advanced metrics, and interactive visualizations for actionable intelligence.

Investor Takeaways

• Demonstrates ability to synthesize large datasets into actionable insights.

• Showcases end-to-end expertise: data acquisition, cleaning, metric creation, visualization, and insight generation.

• Highlights analytical rigor, attention to detail, and ability to deliver quantifiable results that drive strategic decisions.

• Combines technical skills (Python, Power BI, DAX) with product-oriented storytelling for maximum impact.

Final Thought

This dashboard is more than a visualization; it is a decision-making engine for the Indian FinTech ecosystem, providing clarity on investor behavior, capital flows, sector efficiency, and high-value opportunities. It condenses complex multi-year data into digestible, actionable insights, making it an essential tool for analysts, investors, and founders.