🚗 Logistics, Delivery, and Data

I'm excited to share my latest data project: Logistics Dashboard — where I dove deep into real-world transportation data to uncover performance trends, delivery insights, and operational bottlenecks using SQL, Python, and Tableau.

🔍 Why this project?

Transportation plays a critical role in how goods and people move, yet the data behind it can be messy, complex, and full of untapped insights. I chose this project to challenge myself with real logistics data and transform it into a compelling, actionable story for business decision-makers.

💡 What I Did

  • Cleaned and standardized messy location and vehicle data
  • Integrated multiple datasets and inferred vehicle types from vehicle numbers
  • Created user-friendly labels and fixed inconsistent formatting (lowercase, mixed text, etc.)
  • Built a fully interactive dashboard in Tableau

📊 Dashboard Insights

Logistics Dashboard

📦 Shipment Growth

+10.4% YoY increase with 71% faster delivery times

🛻 Vehicle Distribution

Large trucks made up ~40% of active vehicles

🗺️ Regional Hub

Tamil Nadu emerged as a key logistics hub (1,300+ shipments)

🧰 Cost Analysis

Stable maintenance costs with opportunities for deeper cost/shipment analysis

🔗 Explore It Yourself

This project really deepened my appreciation for combining technical analysis with user-focused storytelling. Data is only powerful when it's clear, actionable, and aligned with business goals.

📌 Challenges Overcome

  • Understanding columns with little documentation
  • Merging datasets with tricky joins
  • Standardizing inconsistent formats and text cases
  • Re-labeling technical vehicle type codes into business-friendly terms

Tech Stack

  • SQL – For initial data exploration and transformation
  • Python (Pandas, Matplotlib) – For deeper analysis and preprocessing
  • Tableau – For interactive dashboards and storytelling

What I Learned

  • Effective data storytelling requires both technical skill and user-centered design
  • Even clean-looking datasets often need rigorous preprocessing
  • The right questions drive more impactful insights than fancy visualizations
  • Combining SQL, Python, and Tableau creates a powerful analytics pipeline