CleanerVersion adds a versioning/historizing layer to your relational DB which implements a "Slowly Changing Dimensions Type 2" behavior

Slowly Changing Dimension type 2 using Hive query language using exclusive join technique with ORC Hive tables, partitioned and clustered hive table performance comparison

Spark implementation of Slowly Changing Dimension type 2

ETL process using Pentaho Data Integration (Kettle), for Sales and Purchases Datamarts from Adventureworks, as the final project from the Data Management course from the Big Data & Analytics Masters @ EAE class of 2021

Dive deep into Slowly Changing Dimensions (SCD) ETL in action with this comprehensive tutorial! In this video, we'll explore how to effectively manage changing data using SQL Server Management Studio (SSMS) and SQL Server Integration Services (SSIS).

Applying data engineering techniques to create data pipeline with Azure Cloud Computing

Designing a pipeline in SSIS

This project involves helping a company's HR department analyze the effectiveness of its employee gender diversity program.

This project documentation was developed as a free project, as a data analyst from the fictional company Sell Boardgames would do in his daily work.

Example of how to use Snapshots in DBT

Slowly Changing Dimension Management

An ETL Data Pipelines Project that uses AirFlow DAGs to extract accessories and jewelry data from PostgreSQL Schemas and the shoes data from a CSV file, load them in AWS Data Lake, transform them with Python script, and finally load them into SnowFlake Data warehouse using SCD type 2.

An simple example of SCD Type 2 using single 'inserted' column.

This repository contains materials from all disciplines of the fourth semester