Notebooks have moved beyond a niche solution at Netflix; they are now the critical path for how everyone runs jobs against the company’s data platform. From creating original content to delivering bufferless streaming, Netflix relies on notebooks to inform decisions and fuel experiments across the company as well as to power its machine learning infrastructure and run over 150,000 jobs against its 100 PB cloud-based data warehouse every day. The goal is to deliver a compelling notebooks experience that simplifies end-to-end workflows for every type of user. To enable this, Netflix is investing deeply in notebook infrastructure and open source projects such as nteract.
Michelle Ufford shares some interesting ways Netflix uses data and some of the big bets the company is making on notebooks, covering architecture, kernels, UIs, and Netflix’s open source collaborations with projects such as Jupyter, nteract, pandas, and Spark.
This session is sponsored by Netflix.
Michelle Ufford leads the big data tools team at Netflix. She specializes in analytics infrastructure and has spent the last decade leading high-impact projects in web-scale environments. Her team is responsible for innovations to improve the usability of Netflix’s 100 PB data warehouse and industry-leading data platform. Previously, she led data engineering, data management, and platform architecture for GoDaddy, where she set a TPS record for SQL Server and helped pioneer Hadoop data warehousing techniques. Michelle is also a published author, patented developer, and award-winning open source contributor. You can find her on Twitter at @MichelleUfford.
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