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Addressing The Challenges Of Component Integration In Data Platform Architectures

30 min • 27 november 2023

Summary

Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. One of the core complexities that needs to be addressed is the fractal set of integrations that need to be managed across the individual components. In this episode Tobias Macey shares his thoughts on the challenges that he is facing as he prepares to build the next set of architectural layers for his data platform to enable a larger audience to start accessing the data being managed by his team.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management
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Your host is Tobias Macey and today I'll be sharing an update on my own journey of building a data platform, with a particular focus on the challenges of tool integration and maintaining a single source of truth

Interview

Introduction
How did you get involved in the area of data management?
data sharing
weight of history
- existing integrations with dbt
- switching cost for e.g. SQLMesh
- de facto standard of Airflow
Single source of truth
- permissions management across application layers
- Database engine
- Storage layer in a lakehouse
- Presentation/access layer (BI)
- Data flows
- dbt -> table level lineage
- orchestration engine -> pipeline flows
  - task based vs. asset based
- Metadata platform as the logical place for horizontal view

Contact Info

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
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Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA