100% lakehouse coverage
Extend end-to-end data observability to 100% of your production delta and non-delta tables with a no-code implementation process.
Partners: Databricks
Monte Carlo + Databricks
Data Observability for the Data Lakehouse Platform
Better Together
Resolve incidents quickly
Equip your data team with the context they need to quickly resolve data anomalies and incidents in your lakehouse—before they impact the business.
Drive data adoption
With greater data trust, Monte Carlo enables teams across your organization to develop more data, analytics, and AI use cases on Databricks.
Data Observability for the Data Lakehouse Platform
Monte Carlo makes it easy for organizations that have unified data, analytics, and AI use cases on Databricks to detect and resolve data quality incidents before they impact the business.
Automate monitoring & testing across your lakehouse
Monte Carlo’s ML-powered detection automatically monitors 100% of your delta and non-delta tables for freshness, volume, and schema change incidents, and equips your team to deploy quality monitors and custom rules for your most critical assets.
Monte Carlo adds important capabilities: data producers and consumers can create custom monitors, use anomaly detection algorithms and incident management to deliver their data products.
Matheus Espanhol,
Data Engineering Manager
Data Engineering Manager
Extend lineage across your data stack
Monte Carlo automatically extends Unity Catalog lineage across your stack and down to your BI tools, enabling your team to triage and prioritize data incidents before they impact your data consumers and stakeholders.
Monte Carlo’s end-to-end lineage helps the team draw these connections between critical data tables and the Looker reports, dashboards, and KPIs the company relies on to make business decisions.
Satish Rane,
Head of Data Engineering
Head of Data Engineering
Automate root cause analysis
Monte Carlo equips teams with the context they need in a single interface and automatically identifies potential root cause to expedite incident resolution.
Data-driven decision making is a huge priority for Ibotta, but our analytics are only as reliable as the data that informs them. With Monte Carlo, my team has the tools to detect and resolve data incidents before they affect downstream stakeholders.
Jeff Hepburn,
Head of Data
Head of Data
Ready to accelerate the adoption of data, analytics, and AI built on Databricks?
Talk to an expert
Building a Data Mesh
BairesDev implemented data mesh with Databricks and Monte Carlo at the core of the stack to ensure trustworthy & reliable data that consumers could trust.
Extend Unity Catalog Lineage
Quickly assess the data health and relationships of your Databricks tables and downstream BI dashboards with automated visualization of lineage.
Observability for the Data Lakehouse Platform
With Monte Carlo and Databricks’ partnership, data teams can ensure that these investments are leveraging reliable, accurate data at each stage of the pipeline.
