Push vs Pull Analytics
Push vs pull analytics describes two delivery models for data: pull, where people go look at dashboards and run queries; and push, where the system sends insights and alerts to people when something warrants attention.
In Depth
Pull analytics depends on a fragile assumption: that someone checks the dashboard at the right moment. In practice dashboard views decay within weeks of launch, and the metric drops on the day nobody looks. Push analytics removes the dependency on human routine—the system monitors the data and delivers the finding to where people already are: a Slack channel, an inbox, a webhook into another tool. The mature setup uses both: pull for deliberate exploration and deep dives, push for anything where the cost of noticing late is high. If a metric mattering means someone must act on it within hours, it should be pushed, not polled.
How AI for Database Helps
AI for Database covers both: pull answers and dashboards on demand, and push via workflows that watch your database and send Slack, email, or webhook notifications automatically.
Related Terms
Alerting
Automated notifications triggered when database metrics or query results meet specified conditions or thresholds.
Threshold Alert
A threshold alert is an automated notification that fires when a monitored metric crosses a defined boundary—revenue below a floor, error counts above a ceiling, inventory under a minimum.
Database Webhook
A database webhook is an HTTP callback triggered by a database condition—such as a new row, a changed value, or a threshold crossing—that pushes the event to an external system in real time.
Dashboard Auto-Refresh
Dashboard auto-refresh is the automatic re-running of a dashboard's underlying queries on a schedule, so the displayed metrics stay current without anyone manually reloading or rebuilding anything.
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