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The Library is where the building blocks behind every saved view are managed — kernels, canvases, and workflows. The Library showing kernel, canvas, and workflow counts with recent items The overview opens with a count of each:

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Kernels

A kernel is a named, saved query. Each has a path-style name, a one-line description, and an attribution:
Kernels shipped with the product are marked built-in and attributed by Origin. Ones your team writes carry your own attribution and can be edited.

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Why deterministic matters

The Analytics Graph answers free-form questions, and two similar questions can produce differently shaped answers. A kernel is pinned. That makes kernels the right tool when a number has to be comparable over time — a weekly report, a compliance figure, a widget on a shared dashboard — and the chat interface the right tool for open-ended investigation.
A good working pattern: explore in Dashboard until you have a question worth tracking, then capture it as a kernel so the answer stays stable and can be dropped onto a canvas.

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Built-in kernels worth knowing

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Canvases

A canvas is a multi-widget view assembled from kernels. Each entry shows its name, description, kernel count, and age:
That kernel count tells you how much is behind a canvas before you open it, and which kernels to check if a widget shows something unexpected. The same canvas is reachable from two places, and the difference matters:
Not every canvas follows scope. Widgets reporting tenant-wide figures — Token spend is the built-in example — ignore the current scope by design.
Before building a new one, check the built-in six — Security posture, AI usage overview, Adoption & concentration, Shadow AI, Tools & resources, and Token spend already cover the most common governance, adoption, and cost questions.