A comprehensive guide to building a modern data warehouse with SQL Server, including ETL processes, data modeling, and analytics.

Arcane Insight is a data analytics project designed to harness the power of SQLMesh & DuckDB to collect, transform, and analyze data from Blizzard’s Hearthstone API. Focused on card statistics and attributes, this project reveals detailed insights into card mechanics, strengths, and trends to support BI and strategic analysis.

A production-ready PySpark project template with medallion architecture, Python packaging, unit tests, integration tests, CI/CD automation, Databricks Asset Bundles, and DQX data quality framework.

Building a modern data warehouse with SQL server, including ETL processes, data modeling, and analytics.

'Talk to Your Factory' demo leveraging Edge (Azure IoT Operations), Cloud (Microsoft Fabric), and a Factory Agent (Azure OpenAI), to streamline factory operations. It allows real-time, natural language communication with factory systems, helping operators quickly identify issues, boost efficiency, and minimize downtime.

Databricks DLT Apparel Pipeline Project: Learn medallion architecture, streaming, and data engineering with Delta Live Tables. Includes synthetic data, step-by-step guide, and certification prep.

This project implements a Lakehouse Medallion Architecture using modern Data Stack tools such as Fivetran, Snowflake and dbt. The ficticious organization is an e-commerce company.

Revolutionary AI ETL with Medallion Architecture: Zero-touch autonomous & HITL pipelines on Databricks

A cloud-native data pipeline and visualization project analyzing Formula 1 racing data using Azure, Databricks, Delta Lake, Tableau, and Python for insightful EDA and interactive dashboards.

This repo provides a step-by-step approach to building a modern data warehouse using PostgreSQL. It covers the ETL (Extract, Transform, Load) process, data modeling, exploratory data analysis (EDA), and advanced data analysis techniques.

Extract data from many databases of Labor, Invalids and Social Affairs sectors and convert to appropriate structure and format, then upload to shared data warehouse and data mart. Thanks to that, people of state agencies can easily retrieve and analyze data based on the compiled data warehouse.

End-to-end data engineering pipeline with real-time streaming, cloud processing, and analytics. Built with Apache Kafka, Spark, AWS Glue, and Snowflake using Apache Iceberg tables.

The Olympic Dataset Analysis project involves exploring and analyzing historical Olympic Games data, including athletes, countries, medals, sports, and event performance. Using data analytics and visualization techniques, this project uncovers patterns in Olympic history, top-performing countries, and athlete achievements.

End-to-end Azure Data Engineering project using Medallion Architecture, Databricks, Synapse, and Power BI.

Building a Data Lakehouse using the Medallion architecture.

This project involved the development and implementation of a Data Lake architecture to support an AI model capable of generating image captions. The architecture was designed to efficiently ingest, process, and centralized store large volumes of image and text data.

This project demonstrates end-to-end ETL pipelines for HR and people analytics. It uses Oracle Database and Apache Airflow to extract, transform, and load data, and generate reports on workforce metrics.

Implemented enhanced analytics for trip transactions and ride-based data from SQL Server using Medallion Architecture with Azure Data Factory and Databricks.

Building a modern warehouse with SQL Server , including ETL processes , data modeling and analytics.

End-to-end SQL Data Warehouse project implementing the Medallion Architecture (Bronze–Silver–Gold) using T-SQL. Covers data ingestion, cleansing, transformation, and modeling.