What is a data observability platform?

A better way to find and fix bad data, fast.

Why do I need it?

80% Less Data Downtime

30% Time Saved

70% More Data Quality Coverage

Smarter data reliability

Data rarely breaks the way we expect. Don’t define what data should be. Gain full visibility into your data, systems, and code to see what is

A colorful illustration of data lineage.

Find it

Automated machine learning monitors. No code, no guesswork, no oversights.

  • Scale anomaly detection across your pipelines automatically.
  • Deploy deep quality monitors with +50 metrics.
  • Build custom rules for unique business logic. 
  • Ensure consistency across tables and databases.

Mitigate it

Transform your incident response from reactive scramble to proactive service. 

  • Enhance focus with automated impact analysis.
  • Get actionable alerts to the right team.
  • Track incident tickets, severity, and status.
  • Display data product SLAs and health status.

Fix it

+1,000 incidents are resolved in Monte Carlo every day.

  • Understand where incidents originated with cross-system data lineage.
  • Zero in on bad source data with automated segmentation analysis.
  • Discover system failures with metadata monitoring and incident correlation.
  • Surface bad queries and faulty logic with code change insights.

Prove it

Build trust by displaying reliability levels and response times.

  • Show how data reliability levels have changed.
  • Communicate the current health of key assets.
  • Measure your team’s operational response.
  • Drill into insights at the data product and table levels.

Optimize it

Reduce cost and runtimes. Identify pipelines that have become inefficient over time.

  • Get alerted to queries running longer than normal.
  • Uphold performance SLAs. Filter queries related to specific DAGs, users, dbt models, warehouses, datasets and more.
  • Spot and remove pipeline bottlenecks.