306 Odcinki

  1. Sure, you’re responsible, but are you ethical? w/ Partha Srinivasa

    Opublikowany: 14.10.2021
  2. A data analyst, scientist, and engineer walk into a bar...w/ Danielle Oberdier

    Opublikowany: 7.10.2021
  3. Do we have a data infrastructure crisis? w/ Mammad Zadeh

    Opublikowany: 30.09.2021
  4. Fashion Week...but for data w/ Jans Aasman

    Opublikowany: 23.09.2021
  5. How to think about data value w/ Lars Albertsson

    Opublikowany: 16.09.2021
  6. What’s the deal with Reverse ETL? w/ Tejas Manohar

    Opublikowany: 9.09.2021
  7. The Era of Data Usage w/ Mike Ferguson

    Opublikowany: 2.09.2021
  8. Can’t spell BUZZWORDS without BS w/ Kirk Borne of DataPrime AI

    Opublikowany: 26.08.2021
  9. Free-range, grass-fed, open-source data w/ Denise Gosnell of Datastax

    Opublikowany: 19.08.2021
  10. Documents and Clouds and Graphs, Oh My! w/ Emil Eifrem, CEO of Neo4j

    Opublikowany: 12.08.2021
  11. SEASON TWO KICKOFF w/ DJ PATIL

    Opublikowany: 4.08.2021
  12. Special Edition: Panel on Data Architecture at the Knowledge Graph Conference

    Opublikowany: 6.07.2021
  13. SEASON ONE FINALE: Episode 50

    Opublikowany: 3.06.2021
  14. The Future of BI is AI

    Opublikowany: 27.05.2021
  15. Knowledge is Power: Knowledge Management meets Data Management

    Opublikowany: 20.05.2021
  16. Don’t Treat your Data Stack like a Fine Wine

    Opublikowany: 13.05.2021
  17. Data Organization: Reap what you Sow

    Opublikowany: 6.05.2021
  18. What’s the Secret Recipe for DataOps?

    Opublikowany: 29.04.2021
  19. Why it’s time to mesh with your data architecture

    Opublikowany: 22.04.2021
  20. What do they teach at your Data Science U?

    Opublikowany: 15.04.2021

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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>

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