BigDansing: A System for Big Data Cleansing
Summary: BigDansing: scalable big-data cleansing. It lets users express rules declaratively or procedurally and compiles them into distributed transforms with shared scans and specialized joins atop DBMS/MapReduce, delivering up to 100x speedups while preserving repair quality. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zuhair Khayyat (King Abdullah University of Science and Technology)
- 2. Ihab F. Ilyas (University of Waterloo)
- 3. Alekh Jindal (Massachusetts Institute of Technology)
- 4. Samuel Madden (Massachusetts Institute of Technology)
- 5. Mourad Ouzzani (Qatar Computing Research Institute)
- 6. Paolo Papotti (Qatar Computing Research Institute)
- 7. Jorge-Arnulfo Quiané-Ruiz (Qatar Computing Research Institute)
- 8. Nan Tang (Qatar Computing Research Institute)
- 9. Si Yin (Qatar Computing Research Institute)
BibTeX Citation
@inproceedings{khayyat_sigmod15,
title = {{BigDansing: A System for Big Data Cleansing}},
author = {Khayyat, Zuhair and Ilyas, Ihab F. and Jindal, Alekh and Madden, Samuel and Ouzzani, Mourad and Papotti, Paolo and Quiané-Ruiz, Jorge-Arnulfo and Tang, Nan and Yin, Si},
series = {{SIGMOD} '15},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2723372.2747646},
url = {https://dl.acm.org/doi/10.1145/2723372.2747646},
year = {2015}
}
Incoming Citations (Sorted by Pagerank)
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