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https://tamaszilagyi.com/blog/2019/2019-03-05-dbt

No frills data warehousing with dbt

pre code, pre, code { white-space: pre !important; overflow-x: scroll !important; word-break: keep-all !important; word-wrap: initial !important; } ETL with ease Analytics databases more often than not contain a multitude of tables and views, depicting facts, dimensions or aggregate statistics. Responsibility for the underlying data pipelines traditionally belonged to Data Architects or Data Engineers. However modern tools like dbt are lowering the barrier to doing ETL. To use dbt, you only need to be familiar with SQL.



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No frills data warehousing with dbt

https://tamaszilagyi.com/blog/2019/2019-03-05-dbt

pre code, pre, code { white-space: pre !important; overflow-x: scroll !important; word-break: keep-all !important; word-wrap: initial !important; } ETL with ease Analytics databases more often than not contain a multitude of tables and views, depicting facts, dimensions or aggregate statistics. Responsibility for the underlying data pipelines traditionally belonged to Data Architects or Data Engineers. However modern tools like dbt are lowering the barrier to doing ETL. To use dbt, you only need to be familiar with SQL.



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https://tamaszilagyi.com/blog/2019/2019-03-05-dbt

No frills data warehousing with dbt

pre code, pre, code { white-space: pre !important; overflow-x: scroll !important; word-break: keep-all !important; word-wrap: initial !important; } ETL with ease Analytics databases more often than not contain a multitude of tables and views, depicting facts, dimensions or aggregate statistics. Responsibility for the underlying data pipelines traditionally belonged to Data Architects or Data Engineers. However modern tools like dbt are lowering the barrier to doing ETL. To use dbt, you only need to be familiar with SQL.

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