Liam Brannigan
Liam is Lead Data Scientist at Joulen where he builds time series forecasting pipelines for renewable energy management. He communicates about cutting-edge data science with over 10,000 followers on social media. Liam has been a Polars contributor focused on accessibility and documentation for new users. He also created the world's first online course in Polars and has taught over 3,000 learners to date on Udemy and is the Polars instructor on the O'Reilly platform.
Sessions
Data scientists in the real world have to manage messy datasets that evolve over time. New data must be added, old data must be removed and changes to columns must be handled gracefully. Furthermore, many real world datasets grow from a size that works on a laptop to a size that must run on a server. This talk will show that in Python we can meet all these challenges in a simple and scalable way using the delta-rs package to manage the data storage and Polars to read and write the dataset.