Bridging Business Intent and Data: A Benchmark for Automatic Relational Data Product Generation
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Abstract (arXiv)
A data product is designed to address a specific business need by transforming raw data into a curated, usable asset that delivers actionable insights. Despite practical advances in related areas like text-to-SQL and ELT pipelines, there is no comprehensive benchmark for evaluating the end-to-end process of automatically generating such data products from high-level business requests. To fill this gap, we introduce DP-Bench, a first-of-its-kind benchmark for automatic data product creation, built by combining elements from existing ELT and text-to-SQL datasets. We also propose baseline methods using LLMs to generate data products, providing a foundation for future research in bridging natural language business intent and structured data representation. We make the DP-Bench dataset and code available at: https://huggingface.co/datasets/ibm-research/dp-bench.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 5 of its 13 references that are in the map. First posted on arXiv 16 Dec 2025.
Builds on
5 of 13 references.
References · 5
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2025gpt-oss-120b & gpt-oss-20b Model Cardcited by 1,386
- 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 688
- 2025TARGET: Benchmarking Table Retrieval for Generative Taskscited by 17
- 2025ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelinescited by 16
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Citing papers per year: 2026: 1.
1 paper.