Comments (3)
Thanks @Firstero for making me aware of this request.
Can you elaborate on the benefits of using Elementary over native dbt functionalities?
Thanks,
Piotr
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@leniartek Well, For me, all of my DBT projects are ETL tasks that run daily. I want to know the data quality of each model update, and Elementary provides a good monitoring framework for data anomaly detection, DBT testing, and execution statistics of DBT runs. This allows me to better understand any issues in my dbt etl processing and resolve them in a timely manner.
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Support was added here elementary-data/elementary#1378
from dbt-trino.
Related Issues (20)
- Support CASCADE dropping relations
- Solving for large stage depths HOT 3
- Support `CREATE OR REPLACE` HOT 2
- get_relation not working as already_exists HOT 4
- deltalake rename managed table not allowed arised HOT 1
- Failed to connect to Trino cluster using LDAP auth and HTTP connection HOT 3
- Extra credentials in connection HOT 3
- Not able to create snapshot of a model using dbt-trino==1.7.1 HOT 4
- Refactor to use dbt-adapters interface layer HOT 2
- merge_exclude_columns doesn't work
- upgrade to support dbt-core v1.8.0 HOT 1
- Add REPLACE strategy to incremental materialization
- Executing 'dbt docs generate' when the 'where' clause has different combinations of schemas > produces a permission error HOT 3
- Running codegen to generate source yaml fails HOT 1
- Add partition by in configs for incremental materialization HOT 2
- Custom TrinoCredentials support
- Incremental Materialization Macro Uses Variables Before Defined HOT 3
- When running "dbt test --store-fallures" trino reports "destination table XXX already exists" HOT 3
- Support for persist_docs in Starburst Galaxy HOT 1
- __dbt_tmp suffix in table location HOT 2
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