96 Odcinki

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

    Opublikowany: 4.05.2022
  2. Investing in Communities, Differentiating, and Trusting Your Gut with Erica Brescia

    Opublikowany: 27.04.2022
  3. Data on Kubernetes with Kelsey Hightower, Lachlan Evenson, and Patrick McFadin

    Opublikowany: 20.04.2022
  4. Deep Fakes, Responsible Data Science, and Trust with David Danks

    Opublikowany: 13.04.2022
  5. Cloud Innovation, Analytics, and Data Transformation with Monica Kumar

    Opublikowany: 30.03.2022
  6. Data Lakehouses, Interoperability, and Accessibility with Tomer Shiran

    Opublikowany: 16.03.2022
  7. Interoperability, Governance, and Divergent Teams with Prukalpa Sankar

    Opublikowany: 2.03.2022
  8. Trust, Automation, and Trade-Offs with Joseph Jacks

    Opublikowany: 16.02.2022
  9. Open Source, Adoptability, and Name Changes with Martin Traverso

    Opublikowany: 2.02.2022
  10. Season Two Finale and Recap with Open||Source||Data Producer Audra Montenegro

    Opublikowany: 29.10.2021
  11. Embeddings, Feature stores, and MLOps with Simba Khadder

    Opublikowany: 14.10.2021
  12. Abundance, Metadata, and Automation with Mark Grover

    Opublikowany: 30.09.2021
  13. Metadata, Communities, and Architecture with Shirshanka Das

    Opublikowany: 16.09.2021
  14. Data Management Pain Points and Future Solutions for Data Discovery

    Opublikowany: 2.09.2021
  15. ModelOps, ML Monitoring, and Busy Humans with Elena Samuylova

    Opublikowany: 19.08.2021
  16. Cloud-Native, Open-Source, and Collaborative with Eric Brewer and Melody Meckfessel

    Opublikowany: 5.08.2021
  17. MLOps, AIOps, and Data Startups with Jocelyn Goldfein

    Opublikowany: 22.07.2021
  18. Git-Like Branch and Merge for Data with Einat Orr

    Opublikowany: 8.07.2021
  19. Data Discoverability, Products, and User Diversity with Shinji Kim

    Opublikowany: 24.06.2021
  20. Data Observability, Customer-Led Growth, and Confidence with Barr Moses

    Opublikowany: 10.06.2021

4 / 5

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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