Unveiling Challenges for LLMs in Enterprise Data Engineering
Summary: Identifies enterprise-specific obstacles for LLM-driven tabular data engineering—large tables, more complex tasks, and dependence on internal background knowledge. Systematic evaluation shows substantial accuracy degradation and practical limits of current LLMs in real-world enterprise settings. (summarized by gpt-5-mini on Mar 13 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jan-Micha Bodensohn (German National Research Center for Information Technology; Technical University of Darmstadt)
- 2. Ulf Brackmann (German National Research Center for Information Technology; SAP)
- 3. Liane Vogel (Technical University of Darmstadt)
- 4. Anupam Sanghi (Indian Institute of Technology Hyderabad)
- 5. Carsten Binnig (German National Research Center for Information Technology; Technical University of Darmstadt)
BibTeX Citation
@article{bodensohn_vldb26,
title = {{Unveiling Challenges for LLMs in Enterprise Data Engineering}},
author = {Bodensohn, Jan-Micha and Brackmann, Ulf and Vogel, Liane and Sanghi, Anupam and Binnig, Carsten},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {2},
pages = {196--209},
doi = {10.14778/3773749.3773758},
url = {https://doi.org/10.14778/3773749.3773758},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,731 | Mixtera: A Data Plane for Foundation Model Training | 2026 | SIGMOD | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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