We, at California Northstate University, are implementing canvas data v2, but we are finding that unless you use the python client library (which is not an option for us, we have no python developers ...

We wanted a way to import selected data from selected Canvas tables into a Microsoft SQL Server instance in a way that can be scheduled for automation and required the smallest number of dependencies ...

I actually did a v2 of this guide which is canvas data v2 complaint, which is here: https://community.canvaslms.com/t5/Data-and-Analytics-Group/Guide-Using-Canvas-Data-v2-to-download-exports-of-tables...

I'll start by saying I'm only a data guy as required; I wear all the hats here, so I'm far from versed in best practice.  For our import, a csv/tsv was the easiest for me to implement base...

It's not fast because of the async nature, but I just stagger the jobs.  This runs at 7 AM, the sql import runs at 7:30 AM, it's ready to go at 8 and I haven't had an issue yet.

I actually did a v2 of this guide which is canvas data v2 complaint, which is here: https://community.canvaslms.com/t5/Data-and-Analytics-Group/Guide-Using-Canvas-Data-v2-to-download-exports-of-tables...

I'll start by saying I'm only a data guy as required; I wear all the hats here, so I'm far from versed in best practice.  For our import, a csv/tsv was the easiest for me to implement base...

It's not fast because of the async nature, but I just stagger the jobs.  This runs at 7 AM, the sql import runs at 7:30 AM, it's ready to go at 8 and I haven't had an issue yet.

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