Examples of Flink on Azure
Collection of data on Formula One Racing
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
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.
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.
END TO END DATA ENGINEERING PROJECT
An end to End Implementation of the data lakehouse architecture
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.
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 Internship Project Body Fat Estimator Deployed on Azure Cloud Platform
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
Integration of Covid-19 data utilising Azure Data Factory to perform data ingestion, transformation and storage activities. The goal of this guided project was to become familiar with Microsoft Azure technologies, including; Azure Data Factory(ADF), Azure Data Lake Storage Gen2, Azure SQL Database, Azure Blob Storage, Dataflow, Databricks, etc.
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
Azure for End to End Data Science Project
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