Skip to content
View gsujal421's full-sized avatar
  • India
  • 11:59 (UTC -12:00)

Highlights

  • Pro

Block or report gsujal421

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
gsujal421/README.md

👋 Hi, I'm Sujal

I’m a Data Analyst with hands-on experience building data-driven systems that solve real business problems using SQL, Python, and AWS.

🚀 What I’ve Built

  • 📦 Revenue Leakage Detection System → Identified ₹79K+ potential revenue loss using data analysis and business logic
  • 🌧 Weather-Based Delivery Optimization System → Analyzed delivery performance under rainfall conditions, identifying ~40% demand increase and ~75% delivery delays
  • ☁️ Currently building an end-to-end AWS Data Pipeline using S3, Glue, and Athena for scalable data processing and analysis

🛠 Skills

  • SQL | Python (Pandas, NumPy)
  • Data Analysis & Visualization (Tableau, Excel)
  • AWS (S3, Athena, Glue)

🎯 What I’m Focused On

  • Strengthening SQL and cloud-based data workflows
  • Building production-level data projects
  • Preparing for entry-level Data Analyst / Cloud Data roles

📫 Connect with me

Pinned Loading

  1. Weather-Based-Delivery-Optimization-System Weather-Based-Delivery-Optimization-System Public

    Data-driven system analyzing rainfall impact on delivery operations, identifying 40% demand increase and 75% delay rise, deployed via Streamlit.

    Jupyter Notebook

  2. AWS-Customer-Behavior-Analytics-Pipeline AWS-Customer-Behavior-Analytics-Pipeline Public

    AWS-based customer behavior analytics pipeline using S3, Glue, Athena, and SQL to analyze retention, revenue patterns, and customer segmentation.

    Jupyter Notebook

  3. Revenue-Leakage-Analysis-Risk-Identification Revenue-Leakage-Analysis-Risk-Identification Public

    Uncovered ₹79K+ revenue leakage across ₹847K+ transactions by detecting delayed payments, high-risk customers, and refund anomalies using SQL and Python.

    Jupyter Notebook