But, there was a lot more manual intervention needed in this process... sometimes it would pick some and sometimes none at all.
A lot of the time this resulted in multiple tables landing that needed to be cleaned up.
Could you please give examples of what "manual intervention" were needed?
Which are the times when "sometimes none at all"? -- How was the problem discovered? How was the cross-database data comparison achieved?
And when "needed to be cleaned up", what clean up is needed and how did you do it?
Hi, thanks for the questions 😊
I found that when I used more than one transformation rule of the same type eg. two rules for schema I would sometimes see two tables in my destination database. One with the rules in place (upper case the name, add a suffix), and one without. After testing multiple times it wasn’t clear why this was happening. To clean up I simply deleted the table I didn’t need or copied the data into the correctly named one at the database level. Not a deal breaker but more manual intervention than was intended
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