Data Engineering Podcast

Ein Podcast von Tobias Macey - Sonntags

Sonntags

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419 Folgen

  1. Repeatable Patterns For Designing Data Platforms And When To Customize Them

    Vom: 3.4.2022
  2. Eliminate The Bottlenecks In Your Key/Value Storage With SpeeDB

    Vom: 27.3.2022
  3. Building A Data Governance Bridge Between Cloud And Datacenters For The Enterprise At Privacera

    Vom: 27.3.2022
  4. Exploring Incident Management Strategies For Data Teams

    Vom: 20.3.2022
  5. Accelerate Your Embedded Analytics With Apache Pinot

    Vom: 20.3.2022
  6. Accelerating Adoption Of The Modern Data Stack At 5X Data

    Vom: 14.3.2022
  7. Taking A Multidimensional Approach To Data Observability At Acceldata

    Vom: 14.3.2022
  8. Move Your Database To The Data And Speed Up Your Analytics With DuckDB

    Vom: 5.3.2022
  9. Developer Friendly Application Persistence That Is Fast And Scalable With HarperDB

    Vom: 5.3.2022
  10. Reflections On Designing A Data Platform From Scratch

    Vom: 28.2.2022
  11. Manage Your Unstructured Data Assets Across Cloud And Hybrid Environments With Komprise

    Vom: 28.2.2022
  12. Build Your Python Data Processing Your Way And Run It Anywhere With Fugue

    Vom: 21.2.2022
  13. Understanding The Immune System With Data At ImmunAI

    Vom: 21.2.2022
  14. Bring Your Code To Your Streaming And Static Data Without Effort With The Deephaven Real Time Query Engine

    Vom: 14.2.2022
  15. Build Your Own End To End Customer Data Platform With Rudderstack

    Vom: 14.2.2022
  16. Scale Your Spatial Analysis By Building It In SQL With Syntax Extensions

    Vom: 7.2.2022
  17. Scalable Strategies For Protecting Data Privacy In Your Shared Data Sets

    Vom: 6.2.2022
  18. A Reflection On Learning A Lot More Than 97 Things Every Data Engineer Should Know

    Vom: 31.1.2022
  19. Effective Pandas Patterns For Data Engineering

    Vom: 31.1.2022
  20. The Importance Of Data Contracts As The Interface For Data Integration With Abhi Sivasailam

    Vom: 23.1.2022

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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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