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IBM® Databand® is observability software for data pipelines and warehouses that automatically collects metadata to build historical baselines, detect anomalies and triage alerts to remediate data quality issues.
How it works:
1. Collect: Databand automatically collects metadata to gain immediate visibility, so data platform teams have a standard method for customized data quality validations.
2. Baseline: Next, Databand builds historical baselines based on common run and data behaviors, essentially profiling the data pipeline landscape.
3. Alert: Once the historical baseline is established, Databand alerts on anomalies and rules based on deviations relative to the profile and/or rule breaches.
4. Remediate: Lastly, Databand allows you to create smart communication workflows to remediate data quality issues and keep data deliveries on track.
Better Together: Data Quality and Data Observability
Quickly resolve data incidents with Databand. Manage everything from a single dashboard, enabling you to see, respond and resolve issues without delay.
Detect and manage missing operations, failed jobs and run durations with Databand. Handle pipeline growth and avoid surprises, regardless of scale.
Regain your data team's confidence with Databand. Monitor and alert on data SLAs, unexpected column changes and null records before they impact your consumers.
Identify data incidents early. Databand automates anomaly detection, alerting you to delays and unexpected changes.
Break silos and see the full data story with end-to-end lineage. Databand’s tools help you understand data incident impacts on all flows.
Databand aims to make data observability affordable for businesses of all sizes with a tiered pricing model. The three options – Essentials, Standard, and Premium – offer more accessible entry points for SMBs.
Proactively monitor data pipelines and datasets on AWS with ease, as you can deploy IBM Databand from AWS Marketplace.
Explore data observability for IBM watsonx.data that’s built on an open data lakehouse architecture.