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Canvas Data and Analytics

Not sure if this is the correct place to post this information but I want to share a tool that the company we use for institutional analytics, HelioCampus, just released. It is free to use and allows institutions to extract data from Canvas, including instructor and student course activity, and create a series of data visualizations to help inform and assist with decision-making around deployment, training, course development and usage. We are currently using it and it's been really helpful to our Deans and Provost. If you would like to learn more about it or download it, visit https://www.heliocampus.com/lms_explorerkit

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Hi, Beth.  Do you happen to have a copy of the Data Dictionary they say they provide for this?  I am in the middle of a Canvas/Tableau project right now.

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If you fill out the form on this page LMS Explorer Kit Landing Page  a zip file will be downloaded that contains the Data Dictionary. It's called DataSetFieldReference. Hope this helps!

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Hi again, Beth! Hope things are well in your world!

Wondered if you might be able to answer another question for me regarding this platform (I’ve also been communicating with them directly).

I’ve downloaded everything and made some “adjustments” so that it runs the queries against our CanvasDataStore database (SQL database that I’ve had running for a few years, now). I was able to run the query that creates User_Course_Activity and it completed in about 8.5 minutes and resulted in 3.6M rows.

My other one is taking significantly longer (which may be fine). I was just wondering, in your environment, is the Course_Set_Up file larger than your User_Course_Actvity file? I’m just curious if I’ve got a code issue or it’s just that large of a file. We have 33,000 students and about 3,500 staff members in our instance.

Thanks again! Appreciate you posting the original information regarding HelioCampus!

Gene

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Hi Gene, I asked our Helio data guru to weigh in on your question and when he ran our queries the course data set had 11.6k records, and took 8.7 seconds to run in Redshift. The user data set had 185k records and ran for 30 seconds. So the user data set is (and should be) much larger and take longer to run. Your data set looks fairly large and our university is quite smaller in comparison (~5,000 students and 800 employees). It wouldn't be surprising if the greater number of users played a role in the query performance. Hope this helps and glad this post was useful for you. Take care!

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