The Data Stack Show

Un pódcast de Rudderstack

Categorías:

392 Episodo

  1. The PRQL: The Beauty of Commoditization

    Publicado: 26/11/2021
  2. 63: The ETL - ELT Flip With Ciaran Dynes of Matillion

    Publicado: 24/11/2021
  3. The PRQL: What Part of the Data Stack Will Be Commoditized Next?

    Publicado: 19/11/2021
  4. 62: The Internet of Everything with Rob Rastovich of ThingLogix

    Publicado: 17/11/2021
  5. The PRQL: Are you afraid of IOT?

    Publicado: 12/11/2021
  6. 61: What is Data Design? With Kevin Gervais of Touchless

    Publicado: 10/11/2021
  7. The PRQL: Will we ever get rid of the CSV?

    Publicado: 8/11/2021
  8. Data Debrief: The Highs and Lows of Open Source Projects

    Publicado: 5/11/2021
  9. 60: Architecting a Boring Stream Processing Tool With Ashley Jeffs of Benthos

    Publicado: 3/11/2021
  10. Data Debrief: What Open Source Data Projects Have Come Out of Facebook, Whoops, *Meta?

    Publicado: 29/10/2021
  11. 59: Making ETL Optional with Justin Borgman of Starburst Data

    Publicado: 27/10/2021
  12. Data Debrief: Will Enterprise Build The Future of Data Tooling?

    Publicado: 22/10/2021
  13. 58: Data Federation is No Longer The "F" Word with Scott Gnau of InterSystems

    Publicado: 20/10/2021
  14. Data Debrief: Can Tools Help Solve Data Quality Organizational Challenges?

    Publicado: 15/10/2021
  15. 57: Improving Data Quality Using Data Product SLAs with Egor Gryaznov of Bigeye

    Publicado: 13/10/2021
  16. 56: Stream Processing and Observability with Jeff Chao of Stripe

    Publicado: 6/10/2021
  17. 55: Tables vs. Streams and Defining Real-Time with Pete Goddard of Deephaven Data Labs

    Publicado: 29/9/2021
  18. 54: The Center of the Modern Data Stack with Neil Rahilly of Mixpanel

    Publicado: 22/9/2021
  19. 53: What Religion, a Cult, and a Tech Product Have in Common, with Bart Farrell of DoKC

    Publicado: 15/9/2021
  20. 52: Discussing Data Warehouses, Lakes, and Meshes with James Serra of EY

    Publicado: 8/9/2021

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Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

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