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Lakehouse AI announcements at Data and AI Summit 2023

Lakehouse Monitoring

Intelligent data and model monitoring

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Databricks Lakehouse Monitoring allows teams to monitor their entire data pipelines — from data and features to ML models — without additional tools and complexity. Powered by Unity Catalog, it lets users uniquely ensure that their data and AI assets are high quality, accurate and reliable through deep insight into the lineage of their data and AI assets. The single, unified approach to monitoring enabled by lakehouse architecture makes it simple to diagnose errors, perform root cause analysis and find solutions.

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Proactive reporting

Proactive and simplified detection of anomalies in your data and models, reducing time to market and operational costs incurred due to inefficiencies.

Unified tooling from data to ML

Unified tooling from data to ML

Gain complete visibility into all your data and models in a matter of minutes. The auto-generated metrics enable you to measure the impact of your data and ML products more effectively right out of the box.

Automated root cause analysis

Automated root cause analysis

Seamlessly debug data and model quality issues by tracing root cause back to the anomalies. Capabilities such as automated root cause analysis mean less time to value and higher efficiencies in your production pipelines.

Resources

Blog

Lakehouse AI announcements

eBook

Big Book of Machine Learning

Documentation

Introduction to Databricks Lakehouse

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