Unity Catalog, Delta Sharing and Data Mesh on Databricks Lakehouse
Description
In this technical deep dive, we will detail how customers implemented data mesh on Databricks and how standardizing on delta format enabled delta-to-delta share to non-Databricks consumers. - Current state of the IT landscape 1. Data silos (problems with organizations not having connected data in the ecosystem) 2. A look back on why we moved away from data warehouses and choose cloud in the first place 3. What caused the data chaos in the cloud (instrumentation and too much stitching together) ~ periodic table list of services of the cloud - How to strike the balance between autonomy and centralization - Why Databricks Unity Catalog puts you in the right path to implementing data mesh strategy - What are the process and features that enable and end-to-end Implementation of a data strategy - How customers were able to successfully implement the data mesh on out of the box Unity Catalog and delta sharing without overwhelming their IT tool stack - Use cases 1. Delta-to-delta data sharing 2. Delta-to-others data sharing - How do you navigate when data today is available across regions, across clouds, on-prem and external systems 1. Change data feed to share only “dat…
Description from YouTube. Full content on the video page.
More from Databricks
ReleasesDatabricks launches across the Data + AI stack in 90 seconds
Databricks announced LTAP to unify lakebased and lakehouse data, eliminating ETL and enabling a single copy of data for analytical and operational needs. They also introduced Unity AI Gateway for governance, Genie Ontology for enterprise knowledge graphs, and open-sourced Omniant for managing multiple coding agents.
ReleasesIntroducing Omnigent: The Ultimate Meta-Harness for AI Agents
Omnigent is a new open-source meta-harness for AI agents that provides a unified interface for composition, control, and collaboration across multiple models and agent workflows. It enables stateful, data-centric policies for guardrails and allows real-time sharing and steering of live agent sessions with teammates.
NewsHow DEFRA and Natural England Accelerate Peatland Restoration with AI and Databricks
DEFRA and Natural England utilize AI and Databricks to accelerate peatland restoration by automating the mapping of peatland features and peat dams across England. This technology significantly reduces the time required for mapping, enabling faster identification and restoration of these crucial carbon-storing habitats.
NewsAI Stack Explained in 3 Layers (LLM, Agent Harness, Omnigent)
The AI stack now includes a third layer, the meta harness, which sits above individual agent harnesses. This meta harness, exemplified by Databricks' open-sourced Omnigent, allows for routing queries to appropriate agents and orchestrating tasks across multiple agents, enabling seamless interaction and context sharing between them.
NewsWhat’s coming next to Free Edition
Databricks announces the availability of Genie, GPUs, Agent Hooks, Lakehouse, and Lake Flow Designer on its Free Edition. This update provides virtually all of Databricks' production platform features for free, enabling users to learn and build data and AI projects.