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Building a Data Science Capability from Scratch
Victor Hu covers the challenges, both technical and cultural, of building a data science team and capability in a large, global company.
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Data Cleansing and Understanding Best Practices
Casey Stella talks about discovering missing values, values with skewed distributions and likely errors within data, as well as a novel approach to finding data interconnectedness.
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Predictability in ML Applications
Claudia Perlich presents scenarios in which the combination of different and highly informative features can have significantly negative overall impact on the usefulness of predictive modeling.
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SQL Server on Linux: Will it Perform or Not?
Slava Oks talks about SQL Server’s history, high-level architecture and dives into core of I/O Manager, Memory Manager, and Scheduler. Topics include lessons learned and experiences behind the scenes.
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Security War Stories: The Battle for the Internet of Things
Alasdair Allan discusses the security problems when building Internet of Things devices, and the underlying differences between the IoT and the digital Internet that drive those security issues.
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Framing Our Potential for Failure
Michelle Brush discusses modeling complex systems and architectural changes that could introduce new modes of failure, using examples from embedded systems to large stream processing pipelines.
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Automating Chaos Experiments in Production
Ali Basiri discusses the motivation behind ChAP (Chaos Automation Platform), how they implemented it, and how Netflix service teams are using it to identify systemic weaknesses.
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Designing Calm Technology
Amber Case discusses using Calm Technology to design the next generation of connected devices, covering notification styles, compressing information into other senses, and cognitive overhead.
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Looking inside a Race Detector
Kavya Joshi discusses the internals of the Go race detector and delves into the compiler instrumentation of the program, and the runtime module that detects data races.
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Practical Data Synchronization Using CRDTs
Dmitry Ivanov discusses the basic CRDTs implementations in Scala, explaining the advantages of these data structures to solve many synchronization problems as well as their limitations.
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Next-gen Start-up Cultures: Innovating as You Grow
Jim Plush discusses specific culture initiatives, team structures and management ideals that have worked for his team at CrowdStrike, their virtual team structure, the culture team and more.
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Applying Failure Testing Research @Netflix
Kolton Andrus and Peter Alvaro present how a “big idea” -- lineage-driven fault injection -- evolved from a theoretical model into an automated failure testing service at Netflix.
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