Harmonizing ML and Databases: A Symphony of Data (VLDB 2024 Keynote)
Summary: Argues LLMs reshape DB research by enabling natural-language interfaces but demanding semantic data models and richer context to ensure correctness. Proposes LLM-based cost modeling via pretraining and fine-tuning, presents a prototype and research roadmap. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Fatma Ozcan (Google)
BibTeX Citation
@article{ozcan_vldb24,
title = {{Harmonizing ML and Databases: A Symphony of Data (VLDB 2024 Keynote)}},
author = {Ozcan, Fatma},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4556--4556},
doi = {10.14778/3685800.3685918},
url = {https://doi.org/10.14778/3685800.3685918},
year = {2024}
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