Ponder Raises Millions to Deliver Enterprise-ready Pandas

Data science startup Ponder last week announced that it has secured USD7 million in seed funding to bring enterprise-ready machine learning and analytics to more organizations.

Specifically, Ponder is seeking to overcome the usability challenges of Pandas and help make data teams more productive. Pandas is an extremely popular open-source software library designed for data manipulation and analysis in Python.

Limitations of Pandas

Despite being widely used, Pandas is known to have a difficult syntax and a steep learning curve.

Crucially, limitations when working with large datasets mean that it can run into performance problems that can force a rewrite of code.

“We’ve spoken to dozens of data teams at this point, and a universal sentiment was that they use pandas extensively, but run into performance problems at scale, causing them to have to redo their work from scratch,” explained Doris Lee, the chief executive officer of Ponder.”

“With Ponder’s tools, data scientists no longer have to pick between convenience and scale: they can get both,” she said.

Ponder wants to commercialize its popular open-source tools such as Modin and Lux to address Panda’s usability challenges and scale to handle larger data sets.

The appeal that Ponder is dangling is the ability to scale without data teams having to change how they work. Specifically, Modin can function as a “drop-in” replacement, greatly simplifying matters by merely swapping out relevant APIs.

According to Ponder, its technology is currently used across various sectors and includes pharmaceutical companies such as Bristol Myers Squibb and GSK, technology firms Intel and VMware, and even Ford and Tesla. Its open-source tools have been downloaded over two and a half million times in total.

“Ponder’s technology is based on many years of cutting-edge research that we did to bridge usability and scalability in data science tooling,” said Aditya Parameswaran, the president of Ponder and a professor at UC Berkeley.

“And the impact is enormous: we are making scalable data science accessible to millions of data practitioners who live and breathe pandas.”

With the funding, Ponder says it is looking to significantly scale its team this year to meet the rising demand of enterprise customers and to continue growing and supporting the open-source community of users.

Image credit: Ponder.io