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 Data anomaly detection
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Illustration highlighting elements of IBM Databand’s data anomaly detection feature

To remove bad data surprises from your data pipelines and datasets, IBM® Databand® delivers automatic anomaly detection.

Today’s data platform teams are often reactive when data reliability and quality incidents occur, which are typically found by downstream consumers hours or even days later. The data engineering team is blamed, and the damage done can take months to fix.

IBM Databand features machine learning (ML)-powered anomaly detection to immediately flag when a data incident happens. It builds a historical baseline from your data stack’s metadata and uses smart alerting workflows when operations deviate from the baseline. You miss nothing and can act fast.

 
Databand demo tour

Try an interactive product tour of Databand to see how easy it is to create and debug data incident alerts and get started with dashboards and reports.
Benefits
Improve data trustworthiness

Detecting data anomalies from your metadata in real time builds analysts’ trust in their findings, leading to better-informed decisions and improved outcomes.
Ensure continuous accuracy

Out-of-the-box and customizable trigger alerting helps detect anomalies 24/7 and ensure that all data delivered is accurate and ready for consumers.
Retrospectively improve pipelines

Exploring historical pipeline data allows engineers to retrospectively investigate anomalies so they can optimize future pipeline performance.  
What’s included
Anomaly detection dashboard Databand uses ML-powered detection to continuously analyze and monitor your pipeline and dataset metadata for anomalies. Fine tune the alerts shown on your centralized dashboard with adjustable lookback parameters and sensitivity settings.
Alert configuration and management Databand provides a single view for all your alerts prioritized by severity, including out-of-the-box metrics like run durations, task duration, input count and output count. Or, configure custom alerts with your thresholds for process and data quality deviations.
Root cause analysis Databand tracks metadata and logs from task executors so you can access all log and error information in one place. Compare trends on data and code changes to quickly identify the root cause of data anomalies.
Integrations

Databand integrates with the data pipeline and integration tools you already use and love, like Apache Airflow and IBM® DataStage®, for continuous data observability across your data fabric and modern data stack.

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Take the next step

Implement proactive data observability with IBM Databand today so you can know when there’s a data health issue before your users do.

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