Monte Carlo: Data Observability Insights

Access insights to track data governance initiatives and optimize your data environment.

Description:

With Data Observability Insights, data teams can access the synthesized metadata Monte Carlo generates to build dashboards, analyze data platform team performance and even commit to and track SLAs. This level of detail, common in software engineering and DevOps tooling, makes it possible for data teams to understand what data matters most to the business based on usage, access, and data quality checks. Additionally, Insights makes it easy to create and share high-level reporting with CTOs and CDOs, fostering great data trust and ownership across the company.

Sample Tables:
– Detailed data incident data for the trailing 90 days
– List of key tables based on recent usage
– Recurring queries with deteriorating performance in the past 30 days
– And more.

Fields included:
– Incident type
– Incident identification time
– Resolution time
– Expected threshold
– Actual value that resulted in anomaly
– Number of users with queries executed on the table
– Number of read and write queries executed

Expected Workflow: Data Insights is quickly and easily turned on with the help of your Monte Carlo customer success team. You can email your customer success rep directly or email [email protected]

About the Provider

Founded in 2019, Monte Carlo is an automated, end-to-end data observability platform. Our machine learning first solution notifies data teams about issues of: freshness, distribution, volume, schema and lineage across their data ecosystem, helping them to avoid “data downtime.”

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