Data Engineering Podcast

A podcast by Tobias Macey - Sundays

Sundays

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419 Episodes

  1. Navigating Boundless Data Streams With The Swim Kernel - Episode 98

    Published: 9/18/2019
  2. Building A Reliable And Performant Router For Observability Data - Episode 97

    Published: 9/10/2019
  3. Building A Community For Data Professionals at Data Council - Episode 96

    Published: 9/2/2019
  4. Building Tools And Platforms For Data Analytics - Episode 95

    Published: 8/26/2019
  5. A High Performance Platform For The Full Big Data Lifecycle - Episode 94

    Published: 8/19/2019
  6. Digging Into Data Replication At Fivetran - Episode 93

    Published: 8/12/2019
  7. Solving Data Discovery At Lyft - Episode 92

    Published: 8/5/2019
  8. Simplifying Data Integration Through Eventual Connectivity - Episode 91

    Published: 7/29/2019
  9. Straining Your Data Lake Through A Data Mesh - Episode 90

    Published: 7/22/2019
  10. Data Labeling That You Can Feel Good About - Episode 89

    Published: 7/15/2019
  11. Scale Your Analytics On The Clickhouse Data Warehouse - Episode 88

    Published: 7/8/2019
  12. Stress Testing Kafka And Cassandra For Real-Time Anomaly Detection - Episode 87

    Published: 7/2/2019
  13. The Workflow Engine For Data Engineers And Data Scientists - Episode 86

    Published: 6/25/2019
  14. Maintaining Your Data Lake At Scale With Spark - Episode 85

    Published: 6/17/2019
  15. Managing The Machine Learning Lifecycle - Episode 84

    Published: 6/10/2019
  16. Evolving An ETL Pipeline For Better Productivity - Episode 83

    Published: 6/4/2019
  17. Data Lineage For Your Pipelines - Episode 82

    Published: 5/27/2019
  18. Build Your Data Analytics Like An Engineer - Episode 81

    Published: 5/20/2019
  19. Using FoundationDB As The Bedrock For Your Distributed Systems - Episode 80

    Published: 5/7/2019
  20. Running Your Database On Kubernetes With KubeDB - Episode 79

    Published: 4/29/2019

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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.