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SUMMARY:CIS Seminar: "Prioritizing Computation and Analyst Resources in Large-scale Data Analytics"
DESCRIPTION:Data volumes are growing exponentially\, fueled by an increased number of automated processes such as sensors and devices. Meanwhile\, the computational power available for processing this data – as well as analysts’ ability to interpret it – remain limited. As a result\, database systems must evolve to address these new bottlenecks in analytics. In my work\, I ask: how can we adapt classic ideas from database query processing to modern compute- and analyst-limited data analytics? \nIn this talk\, I will discuss the potential for this kind of systems development through the lens of several practical systems I have developed. By drawing insights from database query optimization\, such as pushing workload- and domain-specific filtering\, aggregation\, and sampling into core analytics workflows\, we can dramatically improve the efficiency of analytics at scale. I will illustrate these ideas by focusing on two systems — one designed to optimize visualizations for streaming infrastructure and application telemetry and one designed for high-volume seismic waveform analysis — both of which have been field-tested at scale. I will also discuss lessons from production deployments at companies including Datadog\, Microsoft\, Google and Facebook.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-prioritizing-computation-and-analyst-resources-in-large-scale-data-analytics/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
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