Data Pipeline with Python and PostgreSQL for Data Analysis & Visualization

This repository showcases data projects where I:

• Extracted raw datasets (CSV files)
• Transformed and cleaned them using Python and SQL
• Loaded them into PostgreSQL for structured analysis
• Delivered insights and visualizations through Python plots and Power BI dashboards

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🔹 Tools Used

• PostgreSQL – Data cleaning, and exploratory data analysis (EDA)
• Python – Data cleaning, EDA, and supporting visualizations (Matplotlib/Seaborn)
• Power BI – Polished, interactive dashboards and final presentations

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🔹 Projects

Each project folder includes:

• PostgreSQL scripts for cleaning, transformations, and analysis
• Python notebooks for additional EDA and visualizations
• Power BI reports with interactive dashboards
• Raw data files for full reproducibility

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🔹 Folder Structure

• data/ – Raw data files

  • cafe_sales_proj1.csv
  • hotel_booking_proj2.csv

• postgresql/ – SQL scripts

  • cafe_sales_cleaning_proj1.sql
  • cafe_sales_eda_proj1.sql

• powerbi/ – Power BI dashboards

  • cafe_sales/ (PBIX, screenshots, PDF)
  • hotel_booking/ (PBIX, screenshots, PDF)

• python/ – Jupyter notebooks

  • data cleaning
  • eda

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🔹 Highlights

• Designed and implemented a basic ETL pipeline from raw CSV files
• Conducted in-depth exploratory data analysis (EDA) using Python and PostgreSQL
• Created interactive dashboards in Power BI to communicate insights

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