Consortium admins have always had to bounce between member instances to piece together a system-wide view. We streamlined that. IgniteAI Ask Your Data now answers questions across every Canvas instance in a consortium from a single query, with the right access controls already in place.
What's new
Root-account admins on consortium parents can run queries that span every child instance tagged to that parent. The change reaches every layer of the pipeline: data models recognize the consortium relationship, pipelines aggregate data across tagged instances, and access controls keep consortium-level queries scoped to admins who own the parent account. Instance-level queries are unchanged — admins on individual member instances still see only their own data. The new behavior turns on automatically once instances are tagged to a consortium parent, so there's no migration step and no extra configuration on the member side.
Why it matters
For consortium admins — system leaders, central IT teams, and shared-services analytics owners — comparing course completion, login trends, or content adoption used to mean exporting from each member instance and stitching the pieces together by hand. Now a single question returns consolidated results across the whole consortium, in the same conversational interface admins already use for their own institution. Member instances keep their autonomy; the consortium gets the aggregate view it needs to make decisions. Reports that used to take a week of analyst time can now be a five-minute prompt.
If your Canvas environment is set up as a consortium, all you need to do is open Ask Your Data from the consortium root account and ask a cross-instance question — try comparing student activity, tool usage, or assignment submission across your member instances. Every question you ask helps sharpen the consortium logic, so don't hold back. And if you want to weigh in on a response, leave your feedback with the thumbs up or down button — it's the quickest way to help us keep making this better for everyone.
