I’m reaching to hear what others do and use as best practise.
I use Snowflake as a destination where we incremental deduped transfer our sources tables. These tables arrives in a landing stage. After that data gets copied to it’s resting staged named raw.
In the copy process we have to clone and drop the added technical columns that Airbyte attach to each table. Essentially we want raw to resemble the source 1:1 in order not to confuse the users.
However this daily clone and drop actually takes up a lot of compute tine and ends up costing us a lot of Snowflake credits. Thus is of course strongly related tonthe high number of tables where we need to do this operation.
My question is - has anyone else any experience on transfering data from airbyte shaped tables and into another staging area inan efficient manner in Snowflake?
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Why do you not only create views with the columns your use consume? Or create tables without the column instead of dropping the columns.