PRQL: A Modern Data Transformation Language Empowering Fintech Data Engineering and Analysis

Discover PRQL, a modern data transformation language designed for data analysts and scientists in the fintech industry. Learn how this powerful tool combines relational algebra with the usability of popular libraries like dplyr, Pandas, and LINQ to offer a functional, pipelined query paradigm. Explore PRQL's compact set of orthogonal language constructs that enable seamless composition of complex data pipelines, streamlining data filtering, transformation, and reshaping processes. Understand how PRQL incorporates modern ergonomics like f-strings, @date literals, and a ?? coalesce operator, as well as features such as functions and loop-based iteration. See how PRQL transpiles into SQL, ensuring compatibility with any relational database and allowing fintech organizations to leverage existing infrastructure. Witness interactive examples demonstrating PRQL's adaptability to fintech use cases. Learn about the open-source nature of PRQL and its growing community support. Gain insights from speaker Tobias Brandt, an experienced professional in data science and data engineering with 20 years of experience in quantitative finance, as he shares his expertise in this 39-minute talk presented by The ASF.