Computational Thinking, Inferential Thinking and "Big Data"
Summary: Advocates fusing computational (algorithms, scalability) and inferential (sampling, uncertainty) perspectives for Big Data. Surveys DB/ML directions—distributed inference, subsampling, time–data and inference–privacy tradeoffs—urging joint theory and methods. (summarized by gpt-5-mini on Feb 09 2026)
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