Alejandro Herrera is a Solution Architect at Ponder.
Ponder provides enterprise-ready tools in Python for rapid, flexible experimentation with data at scale. Ponder makes data teams more productive by enabling them to get insights faster with tools they know and love.
Data practitioners are typically forced to choose between tools that are either easy to use (pandas) or highly scalable (Spark, SQL..etc.). Modin, an open source project originally developed by researchers at UC Berkeley, is a highly scalable, drop-in replacement for pandas.
This talk will give an overview of Modin and practical examples on how to use it to effortlessly scale up your pandas workflows.