Case Study: Scalapay cut data-issue support tickets to zero with Elementary

Key results

The challenge

Scalapay's data team fielded a handful of support tickets each week caused by data-quality issues in its dbt pipelines. Diagnosing the root cause of a given issue could take hours or days. The team lacked a systematic way to detect and triage failures before they reached downstream consumers.

The solution

Scalapay adopted Elementary's dbt-native observability, running data-quality and anomaly tests and centralizing test-failure reporting in Elementary Cloud. Alerting and lineage helped the team catch issues earlier and trace them to their source.

The results, in context

After implementing Elementary, Scalapay reduced data-issue support tickets from a few each week to zero, per its data engineer. Elementary's published story also reports time to diagnose data issues dropping from hours or days to minutes. Figures are the company's own published claims, quoted from Elementary's customer story and dated.

Products used