Data Engineering Podcast

A podcast by Tobias Macey - Sundays

Categories:

419 Episodes

  1. Defining A Strategy For Your Data Products

    Published: 10/23/2023
  2. Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable

    Published: 10/15/2023
  3. Using Data To Illuminate The Intentionally Opaque Insurance Industry

    Published: 10/9/2023
  4. Building ETL Pipelines With Generative AI

    Published: 10/1/2023
  5. Powering Vector Search With Real Time And Incremental Vector Indexes

    Published: 9/25/2023
  6. Building Linked Data Products With JSON-LD

    Published: 9/17/2023
  7. An Overview Of The State Of Data Orchestration In An Increasingly Complex Data Ecosystem

    Published: 9/10/2023
  8. Eliminate The Overhead In Your Data Integration With The Open Source dlt Library

    Published: 9/4/2023
  9. Building An Internal Database As A Service Platform At Cloudflare

    Published: 8/28/2023
  10. Harnessing Generative AI For Creating Educational Content With Illumidesk

    Published: 8/20/2023
  11. Unpacking The Seven Principles Of Modern Data Pipelines

    Published: 8/14/2023
  12. Quantifying The Return On Investment For Your Data Team

    Published: 8/6/2023
  13. Strategies For A Successful Data Platform Migration

    Published: 7/31/2023
  14. Build Real Time Applications With Operational Simplicity Using Dozer

    Published: 7/24/2023
  15. Datapreneurs - How Todays Business Leaders Are Using Data To Define The Future

    Published: 7/17/2023
  16. Reduce Friction In Your Business Analytics Through Entity Centric Data Modeling

    Published: 7/9/2023
  17. How Data Engineering Teams Power Machine Learning With Feature Platforms

    Published: 7/3/2023
  18. Seamless SQL And Python Transformations For Data Engineers And Analysts With SQLMesh

    Published: 6/25/2023
  19. How Column-Aware Development Tooling Yields Better Data Models

    Published: 6/18/2023
  20. Build Better Tests For Your dbt Projects With Datafold And data-diff

    Published: 6/11/2023

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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.