What is Alerting?
Alerting is the practice of automatically notifying people or systems when a defined condition is met, such as a failed job, a data quality issue, or a metric crossing a set threshold. Within a data product, alerts are usually tied to specific checks on quality, freshness, or availability, so the team responsible is notified directly instead of finding out once a report or dashboard breaks.
What are the Challenges of Alerting?
Getting alerting thresholds right is the hardest part of the whole exercise for teams. Set them too sensitively and teams drown in false positives until they start ignoring alerts. Set them too loosely, and real problems slip through unnoticed until they eventually surface somewhere far more costly downstream. Alerts also need to reach the right person, which is hard when ownership of data and systems isn't clearly defined.
Business Benefits of Alerting
- Shortens the gap between an issue and action.
- Limits the damage from data or pipeline failures downstream.
- Improves accountability across teams by routing every single alert to a clearly defined owner.
- Builds confidence in reporting by catching errors before they spread any further downstream.
- Frees teams from having to constantly manually check systems for problems every single day.
How Enterprises Can Better Utilise Alerting
Enterprises should tie every alert to a clearly accountable owner or team. Defining alerting rules at the data product level, covering freshness, quality, and availability, catches issues close to the source, well before they ever affect any downstream report. Grouping related alerts and setting sensible thresholds keeps teams responsive and alert, instead of overwhelmed by a constant stream of low-value notifications they ignore. It also helps to review alerting rules periodically, retiring the ones that no longer add any real value to the team.
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