Scaling Generalist Data-Analytic Agents
Authors: name: Shuofei Qiao; name: Yanqiu Zhao; name: Zhisong Qiu; name: Xiaobin Wang; name: Jintian Zhang; name: Zhao Bin; name: Ningyu Zhang; name: Yong Jiang; name: Pengjun Xie; name: Fei Huang; name: Huajun Chen
Published: 2025-09-29 17:23:08

Abstract: Data-analytic agents are emerging as a key catalyst for automated scientific
discovery and for the vision of Innovating AI. Current approaches, however,
rely heavily on prompt engineering over proprietary models, while open-source
models struggle to face diverse-format, large-scale data files and
long-horizon, multi-step reasoning that real-world analytics demands. This
paper introduces DataMind, a scalable data synthesis and agent training recipe
designed to build generalist data-analytic agents. DataMind tackles three key
challenges in building open-source data-analytic agents, including insufficient
data resources, improper training strategy, and unstable code-based multi-turn
rollout. Concretely, DataMind applies 1) a fine-grained task taxonomy and a
recursive easy-to-hard task composition mechanism to increase the diversity and
difficulty of synthesized queries; 2) a knowledge-augmented trajectory sampling
strategy followed by model-based and rule-based filtering; 3) a dynamically
adjustable training objective combining both SFT and RL losses; 4) a
memory-frugal and stable code-based multi-turn rollout framework. Built on
DataMind, we curate DataMind-12K, a high-quality trajectory set spanning
diverse domains, task categories, and data file formats for data-analytic
tasks. Trained on DataMind-12K, our DataMind-14B achieves state-of-the-art with
an average score of 71.16% on multiple data analysis benchmarks, outperforming
the strongest proprietary baselines DeepSeek-V3.1 and GPT-5. Our DataMind-7B
also performs best among all open-source models with a score of 68.10%. We also
incorporate some empirical insights gained from our exploratory trials into the
analysis experiments, aiming to provide actionable insights about agentic
training for the community. We will release DataMind-12K and DataMind-7B,14B
for the community's future research.