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DA-Studio: An Agentic System for End-to-End Data Analysis
June 30, 2026 ยท Grace Period ยท ๐ VLDB 2026
Authors
Yizhe Liu, Shaolei Zhang, Ju Fan
arXiv ID
2606.31423
Category
cs.DB: Databases
Cross-listed
cs.AI
Citations
0
Venue
VLDB 2026
Abstract
Real-world data analysis is a multi-step process over heterogeneous inputs rather than merely producing a final answer. A practical system should autonomously organize multi-step workflows, execute generated code in a sandboxed and controllable environment, and remain inspectable through visible action traces and intermediate artifacts. Existing LLM-based analysis tools, however, often emphasize isolated subtasks, leaving limited support for complete execution-grounded workflows. We present DA-Studio (Data Analysis Studio), an interactive web-based demo system for end-to-end data analysis that is autonomous, sandboxed, and inspectable. DA-Studio integrates an action-structured analysis backend, a sandboxed execution workspace, and a browser interface for task setup, streamed action traces, artifact preview, code editing and rerunning, and report export. Through iterative action generation, code execution, and feedback incorporation, it incrementally constructs executable analysis steps from raw files and natural-language requests while exposing intermediate results and artifacts throughout the process.
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