Traditional ETL is fragile. The modern approach: ELT — load raw data into the warehouse and transform it there. dbt handles that transformation elegantly.
dbt = SQL + Engineering Practices¶
Version control in Git, dependency management (ref()), built-in tests (unique, not_null), auto-generated documentation with a lineage graph, Jinja templating for dynamic SQL.
Snowflake Advantages¶
- Separation of storage and compute
- Zero-copy cloning — production copies in seconds
- Time Travel — historical data up to 90 days back
Data Quality Tests¶
Every model has tests. Custom test: “the total invoice sum does not differ
from the source system by more than 0.1%.” CI/CD automatically runs
dbt test and dbt run.
Modern Data Stack = Simplicity + Quality¶
An analyst with SQL knowledge can build robust, tested pipelines. Revolutionary.
dbtsnowflakeeltdata warehouseanalytics
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