Google Cloud’s data agents promise to end the 80% toil problem plaguing enterprise data teams
2 min read
Summary
Data engineering is the process of getting data ready for use in analytics or AI, which is a tedious task for enterprises.
Google has launched a series of AI agents to automate the entire data lifecycle, including the Data Engineering Agent in BigQuery, which automates complex pipeline creation through natural language commands, eliminating the need for data engineers to write complex code.
The agent can create new data pipelines from natural language requests and modify or troubleshoot existing ones, but engineers can also see the code written by the agent and make additional suggestions to adjust or customise the data pipeline.
Google is building out its agentic AI services with its Gemini Data Agents API, which enables developers to embed Google’s natural language processing and code interpretation capabilities into their own applications, providing a shift towards an extensible platform approach.
This could provide significant competitive advantages in terms of time-to-insight and resource efficiency and raise the baseline expectations for data platform capabilities across the industry.
Organisations should consider pilot programmes for pipeline automation and how they can leverage these foundational services to build domain-specific agents that address their unique business processes and data challenges.