Tobias Brandt
Tobias Brandt is a PRQL Core Contributor and an experienced professional in data science and data engineering with 20 years of experience in quantitative finance. He currently leads teams responsible for portfolio analytics, systems, and data at Argon Asset Management in Cape Town. Tobias has previously presented at industry conferences such as Subsurface Live and PyconZA.
Accepted Talks:
PRQL: A Modern Language for Data Transformation
This talk will introduce you to PRQL, a powerful data transformation language designed specifically for data analysts and engineers. PRQL combines the elegance of relational algebra with the usability of popular libraries like Pandas, Polars, dplyr, and LINQ, offering a functional, pipelined query paradigm with modern ergonomics and expressivity. The talk will highlight PRQL’s adaptability to complex analytical queries, demonstrated through interactive examples in Python.
As a modern replacement of SQL, PRQL is built around the organizing principle of pipelined relational queries, and facilitated by a compact set of orthogonal language constructs. These constructs enable seamless composition of complex data pipelines, streamlining data filtering, data transformation, and data aggregation processes. PRQL incorporates modern ergonomics like f-strings, @date literals, and a ?? coalesce operator, as well features such as functions and loop based iteration that have long been missing from SQL.
Beyond seamlessly transpiling into SQL, PRQL also supports multiple SQL dialects. This ensures compatibility with any relational database and data warehouse and allows you to leverage your existing data infrastructure.
PRQL is a completely open-source (Apache 2.0 licensed) and volunteer-driven project and is committed to staying that way forever. Having gained over 8400 stars on GitHub in just over a year, the community response has been incredibly enthusiastic and encouraging! Join us and learn about the futur of data transformation!
