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