96 Avsnitt

  1. Data Meshes, Fabrics, and Discovery with Zhamak Dehghani, David Thomas, and Shirshanka Das

    Publicerades: 2022-05-04
  2. Investing in Communities, Differentiating, and Trusting Your Gut with Erica Brescia

    Publicerades: 2022-04-27
  3. Data on Kubernetes with Kelsey Hightower, Lachlan Evenson, and Patrick McFadin

    Publicerades: 2022-04-20
  4. Deep Fakes, Responsible Data Science, and Trust with David Danks

    Publicerades: 2022-04-13
  5. Cloud Innovation, Analytics, and Data Transformation with Monica Kumar

    Publicerades: 2022-03-30
  6. Data Lakehouses, Interoperability, and Accessibility with Tomer Shiran

    Publicerades: 2022-03-16
  7. Interoperability, Governance, and Divergent Teams with Prukalpa Sankar

    Publicerades: 2022-03-02
  8. Trust, Automation, and Trade-Offs with Joseph Jacks

    Publicerades: 2022-02-16
  9. Open Source, Adoptability, and Name Changes with Martin Traverso

    Publicerades: 2022-02-02
  10. Season Two Finale and Recap with Open||Source||Data Producer Audra Montenegro

    Publicerades: 2021-10-29
  11. Embeddings, Feature stores, and MLOps with Simba Khadder

    Publicerades: 2021-10-14
  12. Abundance, Metadata, and Automation with Mark Grover

    Publicerades: 2021-09-30
  13. Metadata, Communities, and Architecture with Shirshanka Das

    Publicerades: 2021-09-16
  14. Data Management Pain Points and Future Solutions for Data Discovery

    Publicerades: 2021-09-02
  15. ModelOps, ML Monitoring, and Busy Humans with Elena Samuylova

    Publicerades: 2021-08-19
  16. Cloud-Native, Open-Source, and Collaborative with Eric Brewer and Melody Meckfessel

    Publicerades: 2021-08-05
  17. MLOps, AIOps, and Data Startups with Jocelyn Goldfein

    Publicerades: 2021-07-22
  18. Git-Like Branch and Merge for Data with Einat Orr

    Publicerades: 2021-07-08
  19. Data Discoverability, Products, and User Diversity with Shinji Kim

    Publicerades: 2021-06-24
  20. Data Observability, Customer-Led Growth, and Confidence with Barr Moses

    Publicerades: 2021-06-10

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What can we learn from ai-native development through stimulating conversations with developers, regulators, academics and people like you that drive forward development, seek to understand impact, and are working to mitigate risk in this new world? Join Charna Parkey and the community shaping the future of open source data, open source software, data in AI, and much more.

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