Airbyte is an open-source data integration engine that helps you consolidate your data in your data warehouses, lakes and databases.

Airbyte

TIL of 3 approaches to DWH structure: <https://towardsdatascience.com/how-should-organizations-structure-their-data-c19b66d629e|https://towardsdatascience.com/how-should-organizations-structure-their-data-c19b66d629e>

If you want to jump in the discussion here: <https://airbytehq-team.slack.com/archives/C03909JGQKV/p1649684251565789>

so after thinking about it im not sure where airbyte fits into this as well. are we closer to the Kimball model?

Airbyte does not build a warehouse as an output, it just bring you data sources into your “data lake”

It’s still the task of the user afterward to model that raw data and structure it into a warehouse organisation

The side discussion is that Airbyte could potentially facilitate that process with pre-built structure automatically generated

Here is something to feed your metric layer research... <@U026A2M4NJZ> <https://github.com/dbt-labs/docs.getdbt.com/discussions/1245#discussioncomment-2452666|https://github.com/dbt-labs/docs.getdbt.com/discussions/1245#discussioncomment-2452666>

ahh awesome <@U02TQLAPAJG>. That's exactly why I'm so exited as well. I'm coming from the business intelligence side of things and learnt and applied kimball all my life, that's why the metrics layer is the trend I'm most exited about. Thanks for the share!