DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis
Data journalism, the practice of using data analysis to surface newsworthy stories, depends increasingly on the ability of reporters and investigative journalists to uncover trends, disparities, and accountability narratives. In practice, exploring large structured datasets remains slow and brittle: journalists must navigate hundreds of variables across many datasets over years, understand data coding conventions, and write non-trivial analysis code while hypotheses evolve. Although LLMs are often touted as "ask in English, get SQL/answers," real newsroom workflows expose recurring failures, e.g., schema mismatches and drift, misread domain semantics and units, and silent assumptions. We ...
| Authors | Raquib Bin Yousuf, Harith Laxman, Vitaliy Shkremetko et al. |
|---|---|
| Primary category | cs.AI |
| Published | 2 October 2026 |
| Last updated at source | 2 October 2026 |
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