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Deliver trustworthy and reliable data with continuous data observability

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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.

It’s estimated that we create roughly 33 quintillion bytes of data each day1 (that’s 18 zeros for those counting). This influx of data has created challenges for data-driven organizations, largely because they are not fully prepared for today’s volume of data, the variety of data sources and the complex infrastructure.

IBM Databand is trusted by modern data teams to deliver more reliable and trustworthy data for their business. From broken data pipelines to data quality issues at-rest in your warehouse, Databand’s continuous data observability platform helps detect data incidents earlier, resolve them faster and deliver more trustworthy data to the business.

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.

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Webinar

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Announcement

IBM Cloud Pak for Data 5.0 is here with new features to streamline data sharing, data integration and governance

Features Data incident management

Quickly resolve data incidents with Databand. Manage everything from a single dashboard, enabling you to see, respond and resolve issues without delay.

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Data pipeline monitoring

Detect and manage missing operations, failed jobs and run durations with Databand. Handle pipeline growth and avoid surprises, regardless of scale.

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Data quality monitoring

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.

Explore feature
Data anomaly detection

Identify data incidents early. Databand automates anomaly detection, alerting you to delays and unexpected changes.

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Data lineage and impact analysis

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.

Explore feature
Case study
The Weather Company The Weather Company has moved toward being a data-first organization. This means working with data on ML use cases for customer advertising, personalization and health condition predictions. See how one data team improved their ML engineering practices with data observability. Read the case study
Customer reviews
Resources 2024 Gartner® Magic Quadrant™ for Augmented Data Quality Solutions

Discover why IBM is named a Leader for the 17th time in a row in the 2024 Gartner® Magic Quadrant™ for Augmented Data Quality Solutions.

The top data quality metrics you need to know

Explore the top data quality metrics you can use to measure the data in your environment, along with examples for each of Databand’s data quality metrics.

Better Together: Data Quality and Data Observability

This research brief, written by The Futurum Group, analyzes how data teams can better understand and scale quality and reliable data across an enterprise with the right data quality platform.

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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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More ways to explore Documentation Blog posts Demo center Resources
Footnotes

1Amount of Data Created Daily (2023) (link resides outside ibm.com), Exploding Topics, 03 April 2023