Leverage DQLabs for continuous data quality monitoring with autothresholds, benchmarking, and actionable alerts to manage and monitor your data environment.
Our platform eliminates the need for manual rules and fine tuning by providing you with out-of-the-box adaptive auto thresholds functionality and drift rules configuration capabilities to benchmark and monitor any attributes across your organization.
Get continuous DQ drift monitoring across all of your data by defining 14 types of smart anomaly detections with actionable alerts and notifications that can be integrated with any of your productivity and collaboration tools such as Outlook, Teams, Slack, and more.
DQLabs DQ monitoring capabilities let you create your own behavioral analysis which uses time-series comparisons for multiple attributes, forecasting, analysis, and visualization.
DQLabs helps you to monitor not just the changes made to an attribute or a specific dataset but also the alterations made to a collection of logical structures or schema objects in your data effectively.
The ability for you to compare the data in real-time between the source to target and get a complete picture of your data transformation journey over time.
Duplicate data affects your overall data strategy. DQLabs is powered with advanced ML models which help you to automatically identify, monitor, and remediate duplicates.
Leverage DQLabs for your DataOps, Data Observability use cases and continuously monitor your data quality.
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