Data Science At Scale Everywhere for Everyone
Speaker: Doris Lee – El Dorado Hills, CA, United StatesTopic(s): Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science
Abstract
Over the past decade, the democratization of data science tooling, particularly through Python libraries like pandas and NumPy, has empowered practitioners of all levels to work with data efficiently. Yet, despite the popularity of these tools, they present challenges as practitioners look to scale their workflows to production. In this talk, we explore the limitations of these tools and pain points that data scientists encounter when dealing with data at scale. Next, I will share how we are solving this problem at Ponder, with both our open-source project Modin and our groundbreaking technology that lets anyone run their Python data workflows directly in their databases.
About this Lecture
Number of Slides: 45Duration: 30 minutes
Languages Available: English
Last Updated:
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