Better Together: Change Data Feed in a Streaming Data Flow
Description
Traditional streaming works great when your data source is append-only, but what if your data source includes updates and deletes? At 84.51 we used DLT and Delta Lake to build a streaming data flow that consumes inserts, updates and deletes while still taking advantage of streaming checkpoints. We combined this flow with a materialized view and Enzyme incremental refresh for a low-code, efficient and robust end-to-end data flow. We process around 8 million sales transactions each day with 80 million items purchased. This flow not only handles new transactions but also handles updates to previous transactions. Join us to learn how 84.51 combined change data feed, data streaming and materialized views to deliver a “better together” solution. 84.51 is a retail insights, media & marketing company. We use first-party retail data from 60 million households sourced through a loyalty card program to drive Kroger’s customer-centric journey. Talk By: Mattias Moser, Data Engineer & Architect, 84.51 LLC ; Scott Gordon, Lead Data Engineer, 84.51˚ Here’s more to explore: Production ready data pipelines for analytics and AI: https://www.databricks.com/solutions/data-engineering The Big Bo…
Description from YouTube. Full content on the video page.
More from Databricks
NewsHow AI and Data Keep 2.3 Million Lawns Healthy | TruGreen & Databricks
TruGreen uses Databricks Genie and Lakehouse to manage 2.3 million lawns with AI that optimizes service timing and predicts customer churn using weather, soil, and service data. The system enables non-technical branch managers to take daily actions through customized reports without requiring data expertise.
NewsHow FOX Sports Uses AI to Power Search
Fox Sports rebuilt their search system on Databricks to handle rapidly changing sports information by continuously streaming player, team, and content data into the index while computing real-time trends. The system uses semantic vector search with time-weighted ranking to surface fresh content higher, doubling the rate at which users find what they're looking for.
NewsHow AI Helps Match Doctors With Communities in Need | Databricks for Good
Databricks provides pro bono services and compute discounts to help nonprofits stay lean through its Databricks for Good program. The video demonstrates the Virtue Foundation agent, which uses Genie and interactive hex maps to identify underserved populations and medical facility distribution in Kenya.
NewsOmnigent: Open-Source Meta-Harness for AI Agents | Matei Zaharia
Omnigen is an open-source meta-harness developed by Databricks that acts as an orchestration and control layer to wrap, manage, and combine multiple AI coding agents. The platform introduces contextual security policies, cost controls, multi-agent task routing, and sandbox integrations to enable collaborative workflows and centralized governance.
NewsBuilding Agents on Databricks with Custom Apps and Omnigent
This video demonstrates how to build, update, and govern custom AI agents on Databricks using Agent Bricks, Databricks Apps, and Omnigent. The tutorial shows how to integrate Model Context Protocol servers, track execution with MLflow traces, schedule automated agent tasks, and manage security policies through Unity AI Gateway.
NewsGoverning AI Strategy with Unity AI Gateway
The Unity AI gateway provides centralized monitoring, cost tracking, and governance for enterprise AI models, MCP servers, and coding agents. Administrators can use the platform to set budget limits, configure external providers, and enforce input policies that block personally identifiable information.