Data Engineering Podcast

Podcast autorstwa Tobias Macey - Niedziele

Niedziele

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419 Odcinki

  1. Data Quality Management For The Whole Team With Soda Data

    Opublikowany: 30.03.2021
  2. Real World Change Data Capture At Datacoral

    Opublikowany: 23.03.2021
  3. Managing The DoorDash Data Platform

    Opublikowany: 16.03.2021
  4. Leave Your Data Where It Is And Automate Feature Extraction With Molecula

    Opublikowany: 9.03.2021
  5. Bridging The Gap Between Machine Learning And Operations At Iguazio

    Opublikowany: 2.03.2021
  6. Self Service Open Source Data Integration With AirByte

    Opublikowany: 23.02.2021
  7. Building The Foundations For Data Driven Businesses at 5xData

    Opublikowany: 16.02.2021
  8. How Shopify Is Building Their Production Data Warehouse Using DBT

    Opublikowany: 9.02.2021
  9. System Observability For The Cloud Native Era With Chronosphere

    Opublikowany: 2.02.2021
  10. Making It Easier To Stick B2B Data Integration Pipelines Together With Hotglue

    Opublikowany: 26.01.2021
  11. Using Your Data Warehouse As The Source Of Truth For Customer Data With Hightouch

    Opublikowany: 19.01.2021
  12. Enabling Version Controlled Data Collaboration With TerminusDB

    Opublikowany: 11.01.2021
  13. Bringing Feature Stores and MLOps to the Enterprise at Tecton

    Opublikowany: 5.01.2021
  14. Off The Shelf Data Governance With Satori

    Opublikowany: 28.12.2020
  15. Low Friction Data Governance With Immuta

    Opublikowany: 21.12.2020
  16. Building A Self Service Data Platform For Alternative Data Analytics At YipitData

    Opublikowany: 15.12.2020
  17. Proven Patterns For Building Successful Data Teams

    Opublikowany: 7.12.2020
  18. Streaming Data Integration Without The Code at Equalum

    Opublikowany: 30.11.2020
  19. Keeping A Bigeye On The Data Quality Market

    Opublikowany: 23.11.2020
  20. Self Service Data Management From Ingest To Insights With Isima

    Opublikowany: 17.11.2020

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This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

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