Business-aware data observability
Free to try for 14 days
What it does
Most data teams have a context problem: alerts are firing, pipelines are instrumented, but when something breaks, engineers still scramble to understand whether it matters, who owns it, and what to fix first. Sifflet adds lineage, ownership & downstream impact context to every data quality signal, so teams can move from reacting to deciding. Connect your real stack, run monitors with full lineage context & experience what business-aware data observability actually means for your pipelines.
Does a similar job
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A common open source approach to observability will begin with databases and visualizations for telemetry - Grafana, Prometheus, Jaeger. But observability doesn’t begin and end here: these tools require configuration, dashboard customization, and may not actually pinpoint the data you need to mitigate system risks. Coroot was designed to solve the problem of manual, time-consuming observability analysis: it handles the full observability journey — from collecting telemetry to turning it into actionable insights. We also strongly believe that simple observability should be an innovation…
- CACito – Actionable data observability for data teams2022 · citodata.com · ▲36
Hi HN! We’re Clemens and Felix from Cito - thrilled to show you what we’ve built to help data engineers stay on top of data quality issues. Think Datadog meets Incident.io. Tests in dbt are great when checking whether specific expectations are true, but don’t work well for use cases where data patterns may change over time. When relying on testing alone, data teams regularly face situations where business stakeholders identify data issues in dashboards first, eroding trust. In such situations, understanding the implications of an issue and debugging can be a very manual and time-consuming…
Evidence Embedded AnalyticsDec 2025 · ▲122A modern dev workflow for your most important data products
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