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Achievement: Pull Sharkx2

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Achievement: Pull Sharkx2

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Joyan9/README.md

Hi there, I'm Joyan 👋

Welcome to my GitHub profile!

About Me

  • Data Analyst with a Master’s in Computer Science and hands-on experience transforming complex data into business impact
  • At DataVinci, built automated dashboards and data pipelines that:
    • Increased client ROAS by 20%
    • Significantly reduced infrastructure costs
  • At AUTO1 Group, bridged business and technical teams to:
    • Automate workflows
    • Streamline operational processes
  • Currently seeking full-time opportunities as a Data Analyst or Analytics Engineer

🛠️ Technologies & Tools

  • Python, SQL, JavaScript
  • BigQuery, dbt
  • Looker Studio, Power BI

🚀 Projects

Kisan Call Centre (KCC) Data Processing Pipeline

  • Technologies Used: Python, Apache Spark, Docker, dlt, DuckDB, Jupyter Lab
  • Designed and implemented a scalable microservices-based data pipeline to process 9+ million farmer query records from India's Kisan Call Centre API.
  • Four core services:
    • data ingestion using DLT for incremental/backfill loads
    • Spark-based processing transforming raw data into star schema
    • interactive analytics dashboards
    • comprehensive testing suite
  • Containerized architecture handles high-volume batch processing with configurable data limits and API integration.

Cab Service Data Analysis Project

  • Technologies Used: Excel, SQL, Google Sheets, Looker Studio, Canva
  • Analyzed market penetration patterns across 10 Indian cities
  • Conducted comprehensive analysis of trip volumes, fares, and customer behaviors
  • Identified strategic insights:
  • Uncovered correlation between retention rates and customer satisfaction
  • Revealed operational differences between tourist and business markets
  • Highlighted pricing and service enhancement opportunities
  • Developed actionable recommendations for business growth

BVG M13 Tram Data Engineering Project

  • Technologies Used: Python (DuckDB), SQL, AWS EC2, AWS S3, Parquet
  • Created a data pipeline to collect and analyze data for Berlin tram line M13
  • Extracted data using BVG REST API and filtered as the requirements
  • Used Python for the Extract and Load (EL) process
  • Loaded the results as parquet files into a S3 bucket
  • Scheduled the job on an EC2 instance using the Crontab scheduler.

Dress-Weatherly

  • Fetches hourly weather forecasts from the Open-Meteo API
  • Suggests clothing items for morning, daytime, and evening
  • Adds weather-specific accessories like umbrellas, sunglasses, or windbreakers
  • Sends daily outfit recommendations via email
  • Runs automatically every morning with GitHub Actions
  • Dockerized for easy deployment
  • Includes unit and integration testing

📫 Connect with Me

Pinned Loading

  1. good_cabs_analysis good_cabs_analysis Public

  2. pyspark-learning-journey pyspark-learning-journey Public

    Jupyter Notebook 10 4

  3. 8-weeks-sql-challenge 8-weeks-sql-challenge Public

    Jupyter Notebook

  4. bvg-open-data-project bvg-open-data-project Public

    Data Engineering Project on extracting data from BVG API for a particular Tram line (M13)

    Jupyter Notebook

  5. learning_data_engineering learning_data_engineering Public

    Jupyter Notebook 3