PARTNER CONTENT: For years, data science and engineering teams have faced a familiar challenge: turning vast, messy datasets into timely, reliable insights. Ingesting and preparing data from multiple warehouses and lakes can be laborious, while the growing variety and volume of sources only adds complexity. The result is often a slow, resource-heavy process that risks delaying decisions and stalling innovation.
AI agents are now emerging as a practical way to automate much of this heavy lifting. In a new Q&A video from The Register, host Tim Phillips speaks with Firat Tekiner from Google to explore how BigQuery’s recently announced data engineering agent could transform data pipeline management.
The discussion tackles key questions facing data-driven organizations in 2025. How can AI agents take on tasks that have become too slow and complex for human teams alone? Can they reduce the time from raw data to actionable insight, and prevent valuable opportunities from being missed? And how should businesses think about the evolving role of humans in the loop as autonomous agents take on more of the day-to-day data engineering workload?
Firat explains the design and purpose of these agents, including how they learn, interact, and specialize. He also addresses how to deploy agents in BigQuery environments, ensure they improve over time, and combine their strengths for greater productivity. The conversation offers practical guidance for organizations already managing large-scale analytics, as well as those looking to future-proof their data operations.
If you want to understand how AI agents can streamline your pipelines, free up your experts for higher-value work, and help your business respond faster to change, this is essential viewing.
Watch the full Q&A now and discover how Google BigQuery’s data engineering agents can help you unlock the full potential of your data. Watch here.
