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A comprehensive ETL pipeline and sales analysis project leveraging Microsoft Azure and PySpark, designed to optimize e-commerce sales by providing actionable insights through detailed data analysis.

  • Updated Mar 22, 2024
  • Jupyter Notebook

This repository hosts an Azure Data Factory to perform the ingestion of the official COVID-19 pandemic- and vaccine-data on an Azure SQL Database, and the relevant DDL to create a data model to produce insightful analytics on PowerBI

  • Updated Feb 28, 2023
  • TSQL

Data Engineering Project - Python, PySpark & SQL - Azure Data Factory (ADF), DataBricks, Synapse Analytics, Azure Data Lake Storage (ADLS) Gen2, Power BI, Tableau and Looker Studio

  • Updated Oct 13, 2023
  • Jupyter Notebook

This project demonstrates an ETL pipeline using Microsoft Azure for IMDb Movie Rating Dataset analysis. It covers data extraction from Azure Blob Storage, transformation with Azure Databricks, and loading into Azure SQL using Azure Data Factory. The pipeline automates insights generation and is a practical example of cloud-based data engineering.

  • Updated Mar 22, 2024
  • Jupyter Notebook

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