Data Science at Scale is Challenging.

Pandas is the most popular tool for data science, with millions of dedicated users. With over 600 functions, pandas enables data scientists to quickly and flexibly clean, transform, and summarize data.

But pandas breaks down on large datasets, leading to out-of-memory errors and slow performance. At scale, the only alternative is to use the so-called “big data” frameworks, such as database systems or Spark.

Learn how Ponder's open-source technology solves these challenges by empowering data science at scale!