azure-storage

Collection of Databricks and Jupyter Notebooks

Build a movie recommendation data pipeline using Azure services for efficient data ingestion, transformation, and orchestration. Utilize Azure Blob Storage, Azure Databricks, and Azure Data Factory to implement collaborative filtering and PySpark ML for accurate movie recommendations.

Personal notebook application (simplified clone of OneNote or Evernote)

Azure Databricks Notebook that assigs team members to customers based on a set of criteria

Azure Databricks notebook sample to connect Blob Storage of Azure Log Analytics

This project analyzes credit card transactions using Jupyter Notebook, cleans data, stores it in Azure Blob, and builds Power BI visuals.

A Medallion-architecture pipeline that moves data from Raw → Silver → Gold using Lakehouse, Notebooks, and metadata-driven file processing. Automates ingestion, transformation, and optimized loading into the Gold Data Warehouse.

🚀 Build an end-to-end Azure ML pipeline to prep data, train models, evaluate results, and deploy live prediction APIs efficiently.