Monte Carlo Releases Incident IQ for End-to-End Data Trust
Data teams using Monte Carlo’s Data Observability Platform can collaboratively identify, alert on, and remediate the root cause of data issues.
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Monte Carlo, the data reliability company, released Incident IQ, a new suite of capabilities that help data engineers better pinpoint, address, and resolve data downtime at scale through the Monte Carlo Data Observability Platform. Incident IQ automatically generates rich insights about critical data issues through root cause analysis, giving teams unprecedented visibility into the end-to-end health and trust of their data beyond the scope of traditional data quality solutions.
To help companies eliminate data downtime, Monte Carlo built Incident IQ, an end-to-end solution that conducts root cause analysis for data issues at each stage of the pipeline, from ingestion in the data warehouse or lake to analytics in your business intelligence dashboards. Incident IQ automatically generates historical insights about your data to identify patterns in query logs, trigger investigative follow-on query results, and monitor upstream dependency changes to pin-point what caused the issue to occur.
Developed after reviewing thousands of real data incidents from Monte Carlo customers, Incident IQ gives data engineers access to insights about their code, their data, and their operational environment that allows them to quickly and collaboratively get to the root cause of data problems -- all in a single UI.
With Incident IQ, everything related to the data issue is captured in a timeline with commenting, documentation, and collaboration features to create rich post-mortems. This level of detail, common in software engineering and DevOps tooling, helps data teams learn from past incidents and determine where to allocate future investment. Additionally, Incident IQ makes it easy to create and share high-level incident reporting with CTOs and CDOs.
Core capabilities of Incident IQ include:
- Central UI that connects the dots between correlated causes of data incidents, and surfaces a historical collection of data incidents for quick comparison
- Access to example queries that pull sample data, as well as rich query logs, historical incidents, and quick links to Monte Carlo’s lineage and catalog features, making it possible to identify, root cause, and fix data issues all from the same interface
- Automatic insights based on the statistical correlation between table fields in anomalous records
- Automatic, end-to-end lineage that maps impacted downstream BI dashboards to the furthest upstream tables, helping teams narrow the focus of root cause investigations
- Automatic runbooks and workflows to make the incident resolution and triaging process easy, fast, and collaborative between data engineers and analysts
- Comprehensive query logs that reveal periodic vs. ad hoc queries, changes in query patterns, and more
For details, visit: www.montecarlodata.com.