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scd-type-2

Here are 24 public repositories matching this topic...

This project simulates a real-world enterprise data migration and modernization strategy. It extracts transactional data from a simulated "On-Premise" environment (hosted on AWS EC2), performs heavy distributed processing using a Hadoop/Spark cluster, and ultimately serves the data via a Cloud-Native, serverless architecture to optimize costs .

  • Updated Mar 19, 2026
  • Python

A Data Warehousing project for retail sales using dimension modelling best practices with SCD type 2 on AWS Redshift. Utilizing AWS Lambda, Glue Workflows and Python Shell jobs to create and automate an ELT pipeline where batch data coming into S3 is loaded onto Redshift and necessary transformations are performed to meet requirements.

  • Updated Aug 10, 2023
  • Python

End-to-end Azure Databricks retail data engineering project using Medallion Architecture (Bronze, Silver, Gold). Implements Auto Loader, Unity Catalog, Delta Lake, SCD Type 1 & 2 dimensions, and Fact Orders for analytics-ready star schema modeling.

  • Updated Jan 24, 2026

In this project we'll create real time healthcare patient data pipeline as data source and use arious services and tools like Azure Eventhubs, Azure Databricks, Delta lake and synapse analytics. also, implement medallion architecture, schema evolution and create facts and dimension tables and connect the cleaned and transformed data to PowerBI.

  • Updated Jan 6, 2026

End-to-end data engineering project using AWS S3, Snowflake, and dbt to implement Medallion Architecture with SCD Type 1 & Type 2 logic on Walmart sales data, followed by analytical visualizations using Seaborn and Plotly.

  • Updated Mar 2, 2026
  • Python

End-to-end data engineering project using AWS S3, Snowflake, and dbt to implement Medallion Architecture with SCD Type 1 & Type 2 logic on Walmart sales data, followed by analytical visualizations using Seaborn and Plotly.

  • Updated Feb 25, 2026

Production-style Slowly Changing Dimension (SCD Type 2) pipeline built with Snowflake, dbt, and AWS S3. Demonstrates secure S3 ingestion, layered bronze/silver/gold modeling, dbt snapshots for historical tracking, and analytics-ready views identifying active vs historical records.

  • Updated Jan 10, 2026
  • Python

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