Track 1: Agentic Data Engineering
Day 2 breakout track · For data engineers and platform teams
In this track you'll build an agentic data system end-to-end — from programming Otto with custom rules and agents, to building a carbon-optimized operations scheduling pipeline, to wiring up automation that keeps everything running.
In this lab, you'll help GreenTech Manufacturing tackle a critical sustainability challenge facing their five UK production facilities. The company consumes over 42 million kWh annually running energy-intensive operations, and with UK carbon offset costs at £50/ton CO2, their environmental impact is becoming a significant financial burden. The key insight: the UK's electricity grid carbon intensity swings dramatically throughout the day. Your mission is to build an intelligent forecasting system that learns from 30 days of historical weather and carbon data to predict these low-carbon windows up to 7 days in advance, then identifies which flexible operations can be strategically shifted from high-carbon hours to clean-energy windows.
Prerequisites
- Complete Hands-On Lab: Getting Agentic on Day 1.
Labs
Lab 1: The Modern Lakehouse
Set up a unified lakehouse environment and learn how agentic systems interact with modern storage layers.
Lab 2: Programmatic Agentic Systems
Program Otto with custom rules, commands, and agents — including scheduling constraints and a Data Quality Agent for your manufacturing operations data.
Lab 3: Agentic Automation
Build the carbon + operations optimization pipeline with a single prompt, then wire up scheduling and failure alerting to keep it running on its own.
Questions?
Reach out to your bootcamp instructors or support@ascend.io.