Thingies
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@ -25,6 +25,7 @@ dbtlearn:
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Once you have set this up and the database as well, you can run `dbt debug` to ensure everything is set up correctly and dbt can reach the database.
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Once you have set this up and the database as well, you can run `dbt debug` to ensure everything is set up correctly and dbt can reach the database.
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You should also delete the lines under the `dbtlearn` key in the `dbt_project.yml` file.
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# DBT noisy things below
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# DBT noisy things below
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@ -32,6 +32,3 @@ clean-targets: # directories to be removed by `dbt clean`
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# files using the `{{ config(...) }}` macro.
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# files using the `{{ config(...) }}` macro.
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models:
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models:
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dbtlearn:
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dbtlearn:
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# Config indicated by + and applies to all files under models/example/
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example:
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+materialized: view
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@ -87,7 +87,7 @@ dbt makes sense nowadays because the modern data stack makes transformations wit
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- Intermediate approach between SCD2 and SCD1
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- Intermediate approach between SCD2 and SCD1
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## dbtw overview
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## dbt overview
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- dbt takes care of the T in ETL/ELT.
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- dbt takes care of the T in ETL/ELT.
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- dbt works within the datawarehouse and with SQL.
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- dbt works within the datawarehouse and with SQL.
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@ -99,3 +99,8 @@ dbt makes sense nowadays because the modern data stack makes transformations wit
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- Data from insideairbnb.com/berlin/
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- Data from insideairbnb.com/berlin/
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- The project will use snowflake as a DWH and preset (managed superset) as a BI tool.
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- The project will use snowflake as a DWH and preset (managed superset) as a BI tool.
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## dbt project structure
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- `dbt_project.yml`: header of the project, with stuff like versioning, the default profile for the project, the paths to different folders, etc.
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