This project demonstrates the end-to-end process of building a data pipeline using Azure Synapse Analytics, Azure Data Factory (ADF), Databricks, and Delta Lake to ingest, clean, transform, and store data.

Tokyo Olympics Analysis Using AZURE platform

Tokyo Olympic 2021 Analysis Using Microsoft Azure platform

This is a repository to demonstrate my details, skills, projects and to keep track of my progression in Data Analytics and Artificial Intelligence topics.

Azure data migration project to migrate data from on-prem SQL Server to Azure cloud using meta-data driven approach.

This repository contains a full setup for a Snowflake and Azure Data Factory pipeline, including a detailed README, a sample sales dataset for data ingestion and transformation, and Snowflake-generated analysis charts. It's ideal for learning Snowflake-Azure integration and automating data workflows.

This project creates an end-to-end data pipeline and interactive dashboard for analyzing mutual funds' performance using Microsoft Azure and Power BI. It leverages Azure Data Factory, Data Lake Storage, SQL Database, and Databricks to build a scalable, efficient pipeline, providing real-time insights and data-driven decision-making.

This repository contains resources for mastering Azure Data Factory from scratch, specifically designed for data engineers. The repository includes pipelines, datasets, linked services, data flows, and an input file that can be used as a practical guide to understand and implement various data engineering tasks in Azure Data Factory.

Azure projects - End to End Data Engineering Project with medallion architecture using Azure Data Factory & Azure Databricks. Azure Serverless/Logical DataWarehouse using Azure Synapse Analystics to demo CETAS, Data Modeling, Incremental loading, CDC and Sql Monitoring the data processing connected to Power BI

END TO END DATA ENGINEERING PROJECT

This project exemplifies a robust Azure streaming data solution tailored for fitness data analysis, leveraging Azure's powerful ecosystem to deliver actionable insights and drive informed decisions in health and wellness management.

Data files for azure cloud data engineering project

The future of sustainability and training: involvement and performance of companies and strategic suppliers

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.

Tokyo Olympics Data Analysis: Creating a ETL pipeline using Azure Data Factory to ingest data, transform it using Azure Databricks and querying and building reports using tools like Synapse Analytics and PowerBI

Implemented an end-to-end Azure data engineering solution to process Tokyo Olympics 2021 data, encompassing extraction, transformation, analytics, and visualization.

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