data-bricks

End-to-end data engineering pipeline using Medallion Architecture (Bronze→Silver→Validation→Gold) on Databricks with PySpark, Apache Airflow orchestration and Power BI dashboard

About This project focuses on performing an end-to-end analysis of IPL data using Apache Spark on Databricks. It begins with setting up a Databricks environment, followed by ingesting and exploring the IPL dataset.

End-to-end data pipeline that ingests 12 Transfermarkt football datasets (1.9M+ records) into Azure Data Lake, transforms them through a medallion architecture in Databricks Unity Catalog, and serves analyst-ready KPIs to Power BI.

AI-Powered Movie Recommendation System on Databricks.

use gg colab cleaning data and training, compare and choose the suitable algorithms. Then, create app integrating machine learning and genAI. This app use to recommend top 3 suitable trees should to plant. This projects also has been supported by AI (chatgpt, copilot)

End-to-End E-commerce Medallion Pipeline

Production-style Azure data engineering pipeline demonstrating ETL, data quality, SQL analytics, PySpark, Databricks, Azure Data Factory, and CI/CD.

Azure End To End Data Enginnering Project

🚀 Production-grade sales analytics on Databricks | Medallion Architecture (Bronze→Silver→Gold) | AI-powered dashboards | 97% Genie AI accuracy | Unity Catalog governance | 790 lines of SQL/Python

Movie market trend analysis using Apache PySpark and Databricks — revenue patterns, genre performance, and ratings across 1000 IMDB films (2006–2016)