dbt artifacts
dbt is a SQL-first transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. It helps teams work directly within the warehouse to produce trusted datasets for reporting, ML modeling, and operational workflows.
dbt performs the T (Transform) of ETL (actually ELT) but it doesn’t offer support for Extraction and Load operations. It allows companies to write transformations as queries and orchestrate them in a more efficient way.
Multiple SQL-like databases are supported currently, including: BigQuery, Databricks, Hive, MySQL, Oracle, PostgreSQL, Redshift, Snowflake, SQL Server, Synapse, and Teradata.
For selected targets, Hackolade Studio facilitates the transformation of data in your warehouse with dbt, by letting you generate dbt property files directly from your Hackolade model. This includes model properties files (models.yml) for your transformation models, and source definition files (sources.yml) for the raw tables your models build on. The feature is available in Tools > Forward-Engineering > dbt Property Files.
Hackolade Studio supports
- the generation of dbt schema models with dbt-specific model-level properties, column-level properties, and custom properties to be included in dbt meta.
- the generation of dbt sources.yml files