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Hubert Dulay interviewed our CEO Pete Goddard, CTO Ryan Caudy, and Lead Developer Devin Smith about the origins of Deephaven and its mission to provide a live data stack. Listen to the full interview on his podcast here.

Datanami's Alex Woodie sits down with our CEO, Pete Goddard, to talk about Deephaven's real-time data capabilities and ease-of-use. Of note, Python users can now launch Core using pip. Covering its simple installation, streamlined table operations, and integration with Jupyter, the article highlights Deephaven's accessiblity to all users, despite their level of programming expertise.

Eric and Kostas from The Data Stack Show chat with Pete Goddard, the CEO of Deephaven, Arjun Narayan, co-founder and CEO of Materialize, Jeff Chao, a staff engineer at Stripe, and Ashley Jeffs, a software engineer at Benthos. Together they discuss batch versus streaming, transitioning from traditional data methods, and define “streaming ETL” as they push for simplicity across the board.

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Conquering real-time data is the future of data science - but when it comes to AI, there are several roadblocks to overcome before you get it right. In his article published in Venture Beat, Chip Kent outlines strategies that put you on the easy path towards real-time AI.

If you're a data scientist, and you're not using real-time data yet, you will be soon. In this episode of the Data Science at Home podcast, "Streaming data with ease," Chip Kent and Francesco Gadaleta talk about the imperative of working with real-time data and the challenges that go along with it. A real-time stream by definition is constantly growing - there is no end to your data. Chip and Francesco discuss useful tools and best practices for data scientists and engineers to help navigate this new territory.

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