Eleven quick pulls answered before an analyst reads them

Can AI answer stakeholder data requests?

The first pass, with receipts. When sales asks how many signups came from the webinar, a companion checks whether an existing Metabase question or Hex notebook already answers it, runs it, and replies with the number, the query link and the caveat if the definition is fuzzy. Requests that need new modeling get routed to the team with the investigation started. An analyst’s twenty minutes then goes to the four requests that need one, rather than re-running the webinar query for the ninth time.

Who notices when a dashboard breaks?

Usually the CEO, at the worst moment.

A weekly routine instead: the companion opens the dashboards the company depends on, checks for query errors, empty panels and numbers outside sane bounds, and files what it finds with the failing query linked, before anyone important sees a blank chart. The same sweep lists dashboards nobody has viewed in ninety days, which is how sprawl gets pruned with evidence.

The tracking-plan audit, reported as a diff

Instrumentation drifts: events renamed in code but not in the plan, properties that stopped populating after a release, the same action tracked under three names by three teams. A companion cross-checks the tracking plan against what Segment, PostHog and Amplitude actually received in the last 30 days and reports the drift as a diff. Fixing it is engineering work; discovering it stops costing an afternoon a quarter. For sources with no tracking at all, there is web-to-spreadsheet extraction, worked page by page in extracting tables from websites.

What the data team keeps

Metric definitions, the semantic layer and the models other teams build on stay authored by the data team. A companion runs and checks against the vetted definitions instead, and publishes the result through the weekly metrics routine so stakeholders stop needing to ask at all.

Frequently asked questions