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Watch quick or full product demos on how we help data engineering teams detect, alert, and resolve data incidents before they cause business impacts.
Join us at Data Council Austin ‘23! Data Council is a 3 day, worldwide, community-driven, data science, engineering, analytics & AI event hosted on March 28-30, 2023.
Free for all to attend in person and virtually. Subsurface is the Data Lakehouse Conference where you can hear firsthand from technology leaders. Learn how to innovate with open-source technologies such as Apache Airflow, Dagster, Apache Superset, Apache Druid, Apache Ranger, and more.
Download the free 2023 DATAcated Trends & Predictions report.
Learn how Data Observability is an emerging discipline that studies the health of enterprise data environments.
Watch our CMO, Ryan Yackel, discuss how Databand helps improve data flows for AI/ML models and data applications by improving the mean time to detection and resolution of data incidents.
See how Databand differentiates itself by inspecting data in motion to support advanced use cases for data science and product teams.
See how IBM expanded its data quality capabilities with the acquisition of Databand and its leading data observability offerings. Get the full report now.
Wondering how more data observability leads to better governance? Watch this video recap where you'll learn about why data observability is so crucial and how it affects data governance and data quality metrics.
Read how Shipper detects data incidents from days to minutes with Databand.
Read g2.com peer reviews of the Databand data observability platform.
Read how Trax Retail drastically reduced data incidents and increases customers by 3x.
Data observability is an emerging discipline for studying the health of enterprise data environments, using techniques adapted from governance tools and application performance management. It includes data quality observability, which monitors the quality and timeliness of data. It also includes data pipeline observability, which monitors the quality and performance of data pipelines, including the infrastructure that supports them.
