Using AI Agents for Data Engineering and Data Analysis: A Practical Guide to Claude Code, Google Antigravity, OpenAI Codex, and More (Merced Books on Agentic AI and Data)

AI coding agents can write SQL, build pipelines, and analyze data, but only if you know how to direct them. Most data professionals are still figuring out where agents help, where they hallucinate, and how to get consistent results. This book closes that gap.

Using AI Agents for Data Engineering and Data Analysis is a hands-on guide to working with AI coding agents on real data tasks. You'll use Claude Code, Google Antigravity, OpenAI Codex CLI, and OpenCode to complete exercises that cover the full data workflow: schema design, data ingestion, semantic layer construction, query optimization, governance, exploratory analysis, AI SQL functions, reporting, and automation.

Every chapter includes exercises you can run yourself on Dremio's free trial. The patterns transfer to any SQL platform. Topics include:

Setting up AI coding agents and connecting them to a lakehouse with MCP or agent skills The agent interaction loop: how to prompt, provide context, and verify output Schema design and DDL generation with Iceberg-aware agents Building Bronze, Silver, and Gold views through agent-assisted workflows Query optimization, Reflections, and performance tuning with agent help Row-access policies, column masking, and governance automation Exploratory analysis and ad-hoc investigation using conversational agents AI SQL functions in practice: AI_CLASSIFY, AI_COMPLETE, AI_GENERATE, and LIST_FILES Connecting external agents through the MCP Server and building custom agent skills Automation pipelines that combine agents with orchestration tools Whether you're a data engineer building pipelines, an analyst exploring datasets, or a developer integrating AI into data workflows, this book gives you the exercises, the prompts, and the patterns to start using AI agents productively today.