Quri for data analysts
Last updated 2026-06-15
The short version
A data analyst answers a steady stream of "what happened?" questions and ends up doing manual monitoring that should be automated. Quri watches metrics across your sources for breaks, answers routine questions in plain language, and surfaces what is trackable — so you spend your time on the deep analysis only you can do, not on babysitting dashboards.
What slows data analysts down
- Routine "why did this move?" questions eat the time meant for deep analysis.
- Manual monitoring across sources is tedious and easy to let slip.
- A metric can break between the times you happen to look at it.
How Quri helps
Let Quri watch metrics across sources and ping you on a break.
Learn more: Anomaly detection →Hand off routine questions to plain-language conversational answers.
Learn more: Conversational analytics →See which metrics are trackable across the connected sources.
Learn more: Metric discovery →Get answers grounded in a knowledge graph, not vague guesses.
Learn more: Knowledge-graph grounded answers →
Frequently asked
- I do my own analysis — what does Quri actually offload?
- Quri takes the repetitive load: it watches metrics for breaks and answers routine "what happened?" questions in plain language, so the time you used to spend on manual monitoring and ad-hoc lookups goes back to the deep analysis only you can do.
- How does Quri keep its answers grounded?
- Quri grounds its answers in a knowledge graph built from your connected sources rather than guessing, so the plain-language replies stay tied to your real data and you can trust them enough to hand routine questions over.