mlsanityData to 14 Oct 2026

DA-Studio: An Agentic System for End-to-End Data Analysis

arXiv 2606.31423 ↗First posted 30 Jun 2026cs.DB cs.AIcited by 1

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 5 of its 6 references that are in the map. First posted on arXiv 30 Jun 2026.

Builds on

5 of 6 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025DeepAnalyze: Agentic Large Language Models for Autonomous Data Science19 Oct
  2. 2023TaskWeaver: A Code-First Agent Framework29 Nov

Other references · 3

  1. 2023LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Modelscited by 82
  2. 2025nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflowcited by 23
  3. 2024Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Waycited by 21

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2024DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models
  2. 2026AdaLens: Interactive Storyline for Monitoring and Steering Long-Running Agentic Data Analysis
  3. 2026QwenPaw-Data: Bridging Facts, Methodology, and Execution for Autonomous Enterprise Data Analytics
  4. 2026Evaluating LLM Agents on Automated Software Analysis Tasks
  5. 2024InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks
  6. 2026DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments?
  7. 2025DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle
  8. 2026LongDA: Benchmarking LLM Agents for Long-Document Data Analysis