Unravel Accelerates DataOps Time to Value.  Learn how.

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Flexible Data Quality

Tackle Data Quality Issues At Warp Speed

Automatically integrate and correlate external data quality checks with AI-driven insights


Move fast to triage data quality issues. Eliminate time-consuming manual detective work.

  • Pull data quality check results from other tools into Unravel.
  • Understand the upstream/downstream impact of data quality issues in seconds.
  • Apply automated circuit-breaker guardrails.
  • See all data details in one unified view, in holistic “workload-aware” context.

All data details automatically captured and correlated, with context-aware insights.

Data Quality End-to-End Observability

Have all data details at your fingertips

See all granular data details—in a workload-aware context—in one place. Pull in external data quality checks. One-click drill-down into quality check results, timelines, lineage, partitions, schema, usage, size, users, and more.

Data Quality Actionable Insights

A data check failed. Now what?

Get a holistic view of everything that’s going on with an app that fails a data check. Automated insights let you understand exactly what’s impacted downstream, who may have introduced bad data (and where) upstream, and what your next best step is to remediate the issue.

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“With Unravel, I am sleeping a lot easier than I did a year ago.”

Bob Jackson
Director – Big Data Engineering, Mastercard
Data Quality Proactive Guardrails

Prevent bad data from seeing the light of day

Avoid data quality issues from wreaking havoc downstream. Automated alerts let you know when—and where—quality checks fail. Customizable user-defined, policy-based AutoActions act as a circuit breaker to kill jobs (or even clusters) before bad data corrupts results.

We support the technologies data teams rely on

Data Quality Single Pain of Glass

Integrate external data quality checks into Unravel

Now data teams have observability details about performance, cost, and quality in a single pane of glass. Seamlessly integrate the results of external data checks (Great Expectations, AWS Deequ, Google CloudDQ, Azure Data Factory, Databricks, Snowflake) right alongside performance and cost information. No more jumping from tool to tool.

We help our customers build better data apps and pipelines

30% improvement in app speed, improved cluster utilization, several thousand nodes under management

83% faster troubleshooting translated to 75% faster analytics cycle time
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Automated guardrails enable optimizations for 66% lower instance-related costs across 100,000s of apps


Performance. Cost. Data Quality. Pick Three.