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Rasgo with Patrick Dougherty

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Manage episode 329732566 series 2626943
Content provided by Eric Anderson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Eric Anderson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Eric Anderson (@ericmander) and Patrick Dougherty (@cpdough) talk about Rasgo, the data transformation platform for MLOps that makes generating SQL easy. The team at Rasgo recently open-sourced a package called RasgoQL, that allows users to execute SQL queries against a data warehouse using Python syntax. Tune in to find out how Rasgo aims to bridge an important gap in the Modern Data Stack.

In this episode we discuss:

  • The advantages of offering both a low-code/no-code UI and a Python interface
  • "How can a data scientist, without needing full-time resources from data engineering, be somewhat self-sufficient in data prep and able to deliver those insights without a massive human capital investment needed?"
  • Where Rasgo fits into the world of feature stores
  • Why one Rasgo user took a trip to a wind farm in Texas
  • Eric’s predictions for the future of data prep and transformation

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People mentioned:

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81 episodes

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Rasgo with Patrick Dougherty

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Manage episode 329732566 series 2626943
Content provided by Eric Anderson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Eric Anderson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Eric Anderson (@ericmander) and Patrick Dougherty (@cpdough) talk about Rasgo, the data transformation platform for MLOps that makes generating SQL easy. The team at Rasgo recently open-sourced a package called RasgoQL, that allows users to execute SQL queries against a data warehouse using Python syntax. Tune in to find out how Rasgo aims to bridge an important gap in the Modern Data Stack.

In this episode we discuss:

  • The advantages of offering both a low-code/no-code UI and a Python interface
  • "How can a data scientist, without needing full-time resources from data engineering, be somewhat self-sufficient in data prep and able to deliver those insights without a massive human capital investment needed?"
  • Where Rasgo fits into the world of feature stores
  • Why one Rasgo user took a trip to a wind farm in Texas
  • Eric’s predictions for the future of data prep and transformation

Links:

People mentioned:

  continue reading

81 episodes

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