CleanerVersion adds a versioning/historizing layer to your relational DB which implements a "Slowly Changing Dimensions Type 2" behavior
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Updated
Feb 7, 2019 - Python
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
Applying data engineering techniques to create data pipeline with Azure Cloud Computing
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).
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.
Complete materials for "Data Warehousing and Modeling" uni course: lectures (Inmon, Kimball, Dimensional Modeling, NoSQL), PostgreSQL labs (Star Schema), exam questions, and practical SQL solutions.
DW://master is an interactive educational platform for mastering data warehousing concepts — from core architecture to advanced slowly changing dimensions (SCD), schema design, IBM Watsonx.data lakehouse technology, and SQL aggregation analytics. Features an AI tutor powered by Claude Sonnet 4 that answers questions about each topic in real-time📊.
This repository contains materials from all disciplines of the fourth semester
This project involves helping a company's HR department analyze the effectiveness of its employee gender diversity program.
DE Proyect - Data modeling using SQL (SQL Server)
Projeto de dbt em um sistema de vendas, nesse caso mostra somente as vendas que foram concluidas, aplicando o SCD na camada Marts
Exploring Data Engineering concepts
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.
Designing a pipeline in SSIS
The mercor-ai Slowly Changing Dimensions (SCD) assignment repository
End-to-end sales data warehouse built with Databricks Delta Live Tables. Features automated ETL, change data capture, and medallion architecture. Transforms raw multi-region sales data into analytics-ready dimensional models.
Solution of DW assignment with SSIS. Question2: type-2 slowly changing dimension with incremental loading. Quesiton3: Versioning
Example of how to use Snapshots in DBT
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