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