f1-data-pipeline
dbt-coves
f1-data-pipeline | dbt-coves | |
---|---|---|
1 | 1 | |
23 | 209 | |
- | 3.8% | |
6.8 | 9.2 | |
10 months ago | 4 days ago | |
Python | Python | |
- | Apache License 2.0 |
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f1-data-pipeline
dbt-coves
-
Is there something wrong with me, I hate dbt, what am I missing ?
This just feels like you aren’t using the plentiful tools to make those “mind-numbingly slow” dev steps faster. For ex., using dbt-coves to generate the staging models with casting to types in a couple clicks. And pulling directly from Fivetran tables is just poor practice, with the additional steps needed to do it “right” being inconsequential at best.
What are some alternatives?
dbt2looker - Generate lookml for views from dbt models
sqlmesh - Efficient data transformation and modeling framework that is backwards compatible with dbt.
astro - Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow. [Moved to: https://github.com/astronomer/astro-sdk]
dbt-ml-preprocessing - A SQL port of python's scikit-learn preprocessing module, provided as cross-database dbt macros.
steam-data-engineering - A data engineering project with Airflow, dbt, Terrafrom, GCP and much more!
magic-the-gathering - A complete pipeline to pull data from Scryfall's "Magic: The Gathering"-API, via Prefect orchestration and dbt transformation.
datavault4dbt - Scalefree's dbt package for a Data Vault 2.0 implementation congruent to the original Data Vault 2.0 definition by Dan Linstedt including the Staging Area, DV2.0 main entities, PITs and Snapshot Tables.
weather_data_pipeline - This is a PySpark-based data pipeline that fetches weather data for a few cities, performs some basic processing and transformation on the data, and then writes the processed data to a Google Cloud Storage bucket and a BigQuery table.The data is then viewed in a looker dashboard
prefect-deployment-patterns - Code examples showing flow deployment to various types of infrastructure
astro-sdk - Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow.