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Learn how to build efficient database-like applications in Julia through a conference talk that showcases a long-running medical financial modeling system. Discover the evolution from JuliaDB.jl to DataFrames.jl, handling large datasets with 100+ columns and 10GB+ models while maintaining quick response times for user queries. Explore the architecture of a production system that has been running since 2015, including implementation details for filtering, grouping, transforming, and joining data. Gain practical insights into optimizing data-heavy Julia applications, making them both performant and stable for end-users. Follow along with real-world examples from GLCS.io that demonstrate how Julia can be effectively deployed in industry settings, particularly for complex financial modeling and data analysis tasks.
