Distil Networks Data Scientist
High-volume data analysis can quickly become computationally and practically expensive. Fortunately, we can benefit from decades of research in streaming algorithms: single-pass, approximate algorithms with bounded memory requirements and quick computation.
This talk introduces some of the major streaming approaches to:
- approximate counting
- the count-distinct problem
- most frequent items
- approximate percentiles
Though discipline is quite mathematical, this presentation will focus on intuitive explanations of the clever underlying logic behind these approaches. Attendees should also leave with some practical ideas about how approximate streaming algorithms can be applied.