Deep Dive into the Latest Lakehouse AI Capabilities

With a unified data & ML platform approach, Databricks has a unique approach to machine learning. By breaking down the silos between the data stack, ML stack and DevOps stack, Databricks offers a simplified, faster, and better-governed way to do ML, including integrated feature engineering and governance tooling, end-to-end tracking and lineage of models and data, automatic monitoring, and root cause analysis. All these capabilities, which typically require six different tools and vendors, are all unified on one platform: Databricks. This saves significant time and resources while accelerating innovation.

In this session you will learn about:
Built-in governance, lineage and monitoring across model, feature and data
Unified feature engineering
Monitoring across your data and ML assets, with automatic reporting and root cause analysis
Deep integration with the data in lakehouse to accelerate the development

Talk by: Ankit Mathur and Nicolas Pelaez

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