Catalog & Cocktails: The Honest, No-BS Data Podcast

A podcast by data.world - Thursdays

Thursdays

Categories:

306 Episodes

  1. A layered approach to data meaning and measurement w/ Nick Handel

    Published: 4/28/2022
  2. S3E16 Takeaways with Nick Handel

    Published: 4/28/2022
  3. Everybody’s an imposter sometimes w/ Steve Perry

    Published: 4/21/2022
  4. S3E15 Takeaways with Steve Perry

    Published: 4/21/2022
  5. Why are we so bad at this modern data stack? w/ Chad Sanderson.

    Published: 4/14/2022
  6. S3E14 Takeaways with Chad Sanderson

    Published: 4/14/2022
  7. Can data policy drive data productivity? w/ Nong Li

    Published: 4/7/2022
  8. S3E13 Takeaways with Nong Li

    Published: 4/7/2022
  9. The future of data is knowledge w/ Bob Muglia

    Published: 3/31/2022
  10. S3E12 Takeaways with Bob Muglia

    Published: 3/31/2022
  11. Agile like a fox, but for data. W/ Shane Gibson from AgileData.io

    Published: 3/17/2022
  12. S3E11 Takeaways with Shane Gibson

    Published: 3/17/2022
  13. Your privacy is my currency with Patricia Thaine from Private AI

    Published: 3/10/2022
  14. S3E10 Takeaways with Patricia Thaine

    Published: 3/10/2022
  15. Are you swimming upstream by not streaming data? w/ Arjun Narayan from Materialize

    Published: 3/3/2022
  16. S3E9 Takeaways with Arjun Narayan

    Published: 3/3/2022
  17. Why are data transformations such a big deal? Live from the dbt Coalesce Happy Hour.

    Published: 2/24/2022
  18. The easiest data is always the hardest to model w/ Karen Lopez

    Published: 2/17/2022
  19. S3E7 Takeaways with Karen Lopez

    Published: 2/17/2022
  20. The three most important letters in data & analytics are W-H-Y w/ Luke Slotwinski from Prologis

    Published: 2/10/2022

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<p>Catalog and Cocktails is an honest, no-BS, non-sales-y conversation about data and analytics. This is your unfiltered chat about everything interesting in data and metadata management, DataOps, architecture, and beyond. Join Juan Sequeda and Tim Gasper to explore emerging topics and hear from visionary leaders across the data space. </p>