DataDazzle: Intelligent Data Exploration through Natural Language
Summary: Demo of DataDazzle, a natural-language data exploration system that lets users query databases without SQL. It emphasizes deployment realities, supports answer review/verification, and provides recommendations for end-to-end NL data exploration beyond accuracy-focused Text-to-SQL. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Mike Xydas (Athena Research and Innovation Center in Information, Communication and Knowledge Technologies; National and Kapodistrian University of Athens)
- 2. Anna Mitsopoulou (Athena Research and Innovation Center in Information, Communication and Knowledge Technologies; National and Kapodistrian University of Athens)
- 3. George Katsogiannis-Meimarakis (Athena Research and Innovation Center in Information, Communication and Knowledge Technologies; Grenoble Alpes University)
- 4. Chris Tsapelas (Athena Research and Innovation Center in Information, Communication and Knowledge Technologies; National and Kapodistrian University of Athens)
- 5. Stavroula Eleftherakis (Athena Research and Innovation Center in Information, Communication and Knowledge Technologies; Grenoble Alpes University)
- 6. Antonis Mandamadiotis (Athena Research and Innovation Center in Information, Communication and Knowledge Technologies; Grenoble Alpes University)
- 7. Georgia Koutrika (Athena Research and Innovation Center in Information, Communication and Knowledge Technologies)
BibTeX Citation
@inproceedings{xydas_sigmod25,
title = {{DataDazzle: Intelligent Data Exploration through Natural Language}},
author = {Xydas, Mike and Mitsopoulou, Anna and Katsogiannis-Meimarakis, George and Tsapelas, Chris and Eleftherakis, Stavroula and Mandamadiotis, Antonis and Koutrika, Georgia},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725094},
url = {https://dl.acm.org/doi/10.1145/3722212.3725094},
year = {2025}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 279 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB | 0.00022468369 |
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