From Data Tsunami to Actionable Insights
summary
Augur ingests git URLs into a relational Augur database so repeated analyses are quick, and an 8Knot dashboard built on Python + Dash reads that DB to show concrete metrics: pull request and issue staleness, time-to-first-response, and review-assignment rates. A set of MIT-licensed practitioner guides map goals → metrics (responsiveness, contributor sustainability, org diversity, security) and link to code repos. Tools and visualizations exist, but converting metrics into actions requires goal-setting, community validation, and a reusable data pipeline.
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chapters (14)
- 0:00Welcome
- 1:51Open source metrics challenges
- 3:40Data science workflow
- 8:56Open source data sources
- 13:12Demo: 8knot with Augur
- 15:21Turning data into insights
- 16:47Chaos practitioner guides
- 19:11Metrics for responsiveness
- 21:19Contributor sustainability
- 22:43Diversity and project risk
- 24:30Security metrics
- 25:33Metrics tools
- 26:36Continuous improvement
- 27:44Q&A
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