Why dbt is disrupting ETL & ELT | Census

The traditional Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) methods are being replaced by a new approach called dbt, which offers more flexibility and scalability for data transformation and analytics. The ELT method is better suited for large amounts of simple data transformations, while the ETL method is more suitable for real-time data with complex calculations. Modern tools like Fivetran, Airflow, Stitch, and cloud warehouses like BigQuery, Snowflake, and Redshift make it easier to use these pipelines. However, dbt allows users to create a flexible command-line data pipeline tool that can be quickly programmed, tested, and modified without huge waiting times. With dbt, users can aggregate, normalize, and sort the data as needed, without constantly updating their pipeline and resending data. The author encourages readers to try out dbt for themselves and explore its capabilities.

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