Extreme Streaming: Business Optimization Driving Algorithmic Challenges

Summary: Extreme streaming for business optimization drives algorithmic challenges in ultra-high-volume warehouses. Ingestion at high rates with concurrent updates; outlines high-level mechanisms fusing streaming analytics, data mining, and voice/text data for churn insights. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4035
Venue: SIGMOD
Year: 2008
Pagerank: -
Overall Rank: 13,755 | 5.63%
DOI: 10.1145/1376616.1376619

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Authors

1. William O'Connell, Ph.D. (IBM)

BibTeX Citation

@inproceedings{phd_sigmod08,
        title = {{Extreme Streaming: Business Optimization Driving Algorithmic Challenges}},
        author = {William O'Connell, Ph.D.},
        series = {{SIGMOD} '08},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1376616.1376619},
        url = {https://dl.acm.org/doi/10.1145/1376616.1376619},
        year = {2008}
}

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