Lakehouse Monitoring GA: Profiling, Diagnosing, and Enforcing Data Quality with Intelligence

Databricks Lakehouse Monitoring allows you to monitor all your data pipelines and ML models – without additional tools and complexity. Integrated into Unity Catalog, teams can track quality alongside governance, building towards the self-serve data platform dream. By continuously assessing the profile of your data, Lakehouse Monitoring allows you to stay ahead of potential issues, ensuring that pipelines run smoothly and ML models remain effective over time. We will show you how simple it is to start using monitoring and intelligently prevent quality issues. Join us to discover how Lakehouse Monitoring can help your organization democratize and establish trust in your data today. Talk By: Jacqueline Li, Associate Product Manager, Databricks ; Kasey Uhlenhuth, Sr. Manager, Product, Databricks Here’s more to explore: Data, Analytics, and AI Governance: https://dbricks.co/44gu3YU Connect with us: Website: https://databricks.com Twitter:   / databricks   LinkedIn:   / data…   Instagram:   / databricksinc   Facebook:   / databricksinc  

A Technical Deep Dive into Unity Catalog's Practitioner Playbook
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A Technical Deep Dive into Unity Catalog's Practitioner Playbook

Apps on Databricks: Build Data Applications on Databricks in 20 Minutes!
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Apps on Databricks: Build Data Applications on Databricks in 20 Minutes!

Data Analytics with Microsoft Fabric
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Data Analytics with Microsoft Fabric

Delta Live Tables A to Z: Best Practices for Modern Data Pipelines
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Delta Live Tables A to Z: Best Practices for Modern Data Pipelines

A Practical Introduction to Machine Learning with Databricks Mosaic AI
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A Practical Introduction to Machine Learning with Databricks Mosaic AI

Unity Catalog Workshop: Unified, open governance for data and AI (July 2024)
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Unity Catalog Workshop: Unified, open governance for data and AI (July 2024)

Data Quality and Reliability with Soda Core - Vijay Kiran
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Data Quality and Reliability with Soda Core - Vijay Kiran

RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source
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RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source

Introducing Lakebase - Databricks Co-founder & Chief Architect Reynold Xin
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Introducing Lakebase - Databricks Co-founder & Chief Architect Reynold Xin

GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem
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GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem

Technical Deep Dive for Practitioners: Databricks Unity Catalog from A-Z
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Technical Deep Dive for Practitioners: Databricks Unity Catalog from A-Z

What is Databricks? The Story Behind the Modern Data Platform (Visual Explanation)
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What is Databricks? The Story Behind the Modern Data Platform (Visual Explanation)

Data Warehouse vs Data Lake vs Data Lakehouse | ETL, OLAP vs OLTP
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Data Warehouse vs Data Lake vs Data Lakehouse | ETL, OLAP vs OLTP

30 DLT Data Quality & Expectations | Monitor DLT pipeline using SQL | Define DQ rule |Observability
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30 DLT Data Quality & Expectations | Monitor DLT pipeline using SQL | Define DQ rule |Observability

Learn Practical Techniques for Applying Data Quality in the Lakehouse with Databricks
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Learn Practical Techniques for Applying Data Quality in the Lakehouse with Databricks

Intro to Databricks Lakehouse Platform Architecture and Security
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Intro to Databricks Lakehouse Platform Architecture and Security

Master Data Quality in Databricks with DQX: Ultimate Guide! -  Part 1
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Master Data Quality in Databricks with DQX: Ultimate Guide! - Part 1

Dynamic Databricks Workflows - Advancing Spark
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Dynamic Databricks Workflows - Advancing Spark

Databricks Tutorial | Databricks Free Edition Tutorial with End-to-End Data + AI Project
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Databricks Tutorial | Databricks Free Edition Tutorial with End-to-End Data + AI Project

How Instagram Scaled Postgres to 2 Billion Users
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How Instagram Scaled Postgres to 2 Billion Users