104 Epizód

  1. Metadata, Communities, and Architecture with Shirshanka Das

    Közzétéve: 2021. 09. 16.

  2. Data Management Pain Points and Future Solutions for Data Discovery

    Közzétéve: 2021. 09. 02.

  3. ModelOps, ML Monitoring, and Busy Humans with Elena Samuylova

    Közzétéve: 2021. 08. 19.

  4. Cloud-Native, Open-Source, and Collaborative with Eric Brewer and Melody Meckfessel

    Közzétéve: 2021. 08. 05.

  5. MLOps, AIOps, and Data Startups with Jocelyn Goldfein

    Közzétéve: 2021. 07. 22.

  6. Git-Like Branch and Merge for Data with Einat Orr

    Közzétéve: 2021. 07. 08.

  7. Data Discoverability, Products, and User Diversity with Shinji Kim

    Közzétéve: 2021. 06. 24.

  8. Data Observability, Customer-Led Growth, and Confidence with Barr Moses

    Közzétéve: 2021. 06. 10.

  9. Open Source Data & Its Role in the Future of Technology: Season 1 Recap

    Közzétéve: 2021. 04. 22.

  10. Data Visualization, Democratization, and Javascript with Melody Meckfessel

    Közzétéve: 2021. 03. 25.

  11. DataOps, MLOps, and Self Service: How Data Teams are Changing

    Közzétéve: 2021. 03. 11.

  12. Fabrics, Meshes, and Graphs with Deloitte Principal Dave Thomas

    Közzétéve: 2021. 02. 25.

  13. Metadata, Graphs, and Responsible AI with Paco Nathan

    Közzétéve: 2021. 02. 11.

  14. Data Analytics: Hard Skills vs Soft Skills and the Gift of Thinking Different

    Közzétéve: 2021. 01. 28.

  15. Global Connectivity: Share and Democratize Through Open Data

    Közzétéve: 2021. 01. 14.

  16. From DBA to SRE: 2021 Predictions for Data on Kubernetes

    Közzétéve: 2020. 12. 23.

  17. Open Source’s Impact in Academia with Open@RIT's Stephen Jacobs

    Közzétéve: 2020. 12. 10.

  18. Data Meshes: Big Data Architecture Becoming Distributed, Declarative and Domain Oriented

    Közzétéve: 2020. 11. 25.

  19. Data on Kubernetes: Platform, Resource, and Ecosystem tooling with Microsoft Azure’s Lachlan Evenson

    Közzétéve: 2020. 11. 12.

  20. Data, Kubernetes, and Our Best Selves with Google’s Kelsey Hightower

    Közzétéve: 2020. 10. 29.

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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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