DBTB INT S Srinivasan r
summary
Argues that behavioral analytics must track individual attitude changes over time and that deriving that signal requires ingesting and processing very large volumes of disparate data quickly. Claims the curriculum for big data processing centers on mathematics, statistics, and practical techniques like clustering rather than only domain subject matter, and flags machine learning and legal/privacy considerations as necessary complements for production systems that actually use derived behavioral insights.
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