Examples of Flink on Azure

Collection of data on Formula One Racing

This project builds an End-to-End Azure Data Engineering Pipeline, performing ETL and Analytics Reporting on the AdventureWorks2022LT Database.

Ingested Tokyo Olympic data into Azure Data Lake using Azure Data Factory. Enhanced data quality with Apache Spark on Azure Databricks. Optimized SQL queries on Synapse Analytics, reducing execution time. Developed engaging Power BI dashboards, boosting user engagement creating KPI's with DAX.

Foundation Workspace for Airflow, Spark, Hive, and Azure Data Lake Gen2 via Docker

Azure-based solution for ingesting and analyzing Formula 1 data using Azure Data Lake Storage Gen2 and Databricks

An end to End Implementation of the data lakehouse architecture

The data engineering project aims to migrate a company's on-premises database to Azure, leveraging Azure Data Factory for data ingestion, transformation, and storage. The project will implement a three-stage storage strategy, consisting of bronze, silver, and gold data layers (Medalion architecture). Documentation of the project is in PDF file.

This end-to-end data engineering project demonstrates how to design, build, and orchestrate a complete modern data platform solution using Azure Data Factory, Azure DevOps, and Azure Data Lake Storage Gen2 — following the medallion architecture (Bronze → Silver → Gold).

END TO END DATA ENGINEERING PROJECT

An Internship Project Body Fat Estimator Deployed on Azure Cloud Platform

End-to-End Azure Data Engineering Project demonstrates the implementation of a full-scale, scalable data engineering pipeline leveraging Azure cloud technologies. The project follows the Medallion Architecture to process and transform large volumes of data from multiple sources such as CSV, XLSX, JSON, PostgreSQL, SQL databases, and APIs.

An end-to-end data engineering pipeline that fetches data from Wikipedia, cleans and transforms it with Apache Airflow and saves it on Azure Data Lake. Other processing takes place on Azure Data Factory, Azure Synapse and Tableau.

This project builds an End-to-End Azure Data Engineering Pipeline, performing ETL and Analytics Reporting on the AdventureWorks2022LT Database.

This project presents a scalable end-to-end data pipeline designed for processing and analysing car sales data using the Azure Cloud and Databricks ecosystem.

Ingested earthquake event data from the US Geological Survey (USGS) API for daily intervals and stored raw JSON files in the Bronze layer (Azure Data Lake Storage– ADLS).

🌥️ Build a complete Azure data pipeline for seamless migration, ETL, and analytics from on-premise databases to the cloud, leveraging Power BI for insights.

This repo explains all services provide by azure related to AL-ML services.

The aim of this project is to build a cost efficient Data Warehouse on Amazon's Retail sales data and perform Customer lifetime value analyses.

Learning Azure Data Fundamentals of Relational and Non Relational Data with Microsoft Learn Platform