dbt Builds Data
dbt Builds Data in Euno
Euno tracks build activity across dbt models, sources, snapshots, seeds, and tests. This comprehensive build history enables teams to make informed decisions about model performance, build efficiency, data freshness, and resource utilization across their dbt projects.
Utilize dbt Builds Data To:
Identify performance bottlenecks to optimize slow-running models and improve build times.
Monitor build success rates to ensure data reliability and catch issues early.
Understand resource utilization by analyzing build frequency, duration, and resource consumption.
Track data freshness to maintain up-to-date analytics and reporting.
Understanding the Types of Builds Data Captured in Euno
For relevant dbt resources—including models, snapshots, and seeds—Euno tracks:
Total Builds: Number of times the dbt model was built or refreshed.
Average Build Time: Average duration of a single build, indicating model complexity or runtime.
Total Build Time: Sum of all build durations during the selected period.
Note: This information comes from dbt artifacts uploaded to Euno. If only compiled job data is sent (rather than executed runs), these metrics may not reflect actual build activity.
total_builds_14d
total_builds_30d
total_builds_60d
The total number of times the dbt model was built in the last 14/30/60 days.
dbt models, dbt_seeds
average_build_time_14d
average_build_time_30d average_build_time_60d
Average duration of a single build over the last 14/30/60 days.
dbt models, dbt_seeds
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