AI is only as good as the layer underneath it. That layer in Databricks is called a Metric View: a semantic model that defines your measures, your joins, and the rules for how data fits together.
In this episode, Stefan walks through the full stack end-to-end on a real LEGO dataset: building Metric Views in Databricks, generating them with dbt, deploying through Databricks Asset Bundles, and finally exposing it all through a Genie Space that business users can chat with. Along the way we get into some deeper questions: what the limits of metric views look like, how access control works, what BI "shifting left" actually means for engineering teams, and how you organize this in data products.
If you saw our Snowflake Intelligence episode, this is the Databricks counterpart. The Snowflake episode can be found here: https://www.youtube.com/watch?v=Gp-BntPgpcU
Resources:
- Demo code: https://github.com/datamindedbe/demo-technology-exploration
- [episode-specific links here]
Creators & Guests
- Jonny Daenen - Host
- Stefan Van Raemdonck - Guest
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Click here to watch a video of this episode.
Full playlist: https://www.youtube.com/playlist?list=PLJ_da7qdfL80rA7byzC_CmyrfJWjcCTnb
- (00:00) - Chapter 1
- (00:00) - Intro
- (00:50) - Meet Stefan
- (01:43) - Demo: talking to your LEGO data
- (07:17) - Why semantic layers? Data products explained
- (11:20) - What's in a metric view?
- (14:15) - Creating Metric Views in Databricks
- (16:29) - The LEGO data model
- (18:17) - Data Products & Metric Views in Databricks
- (22:07) - Are we limited to predefined measures?
- (23:16) - Building: native Databricks SQL bundles
- (29:12) - Building: dbt
- (31:16) - Maintenance and BI shifting left
- (33:59) - Deploying dbt on Databricks
- (35:29) - Creating the Genie Space
- (38:24) - Access Control and Permissions in Data Queries
- (39:28) - Writing SQL on top of Metric Views
- (40:10) - Takeaways and favorite Lego
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Data & AI: Technology Explorations is a biweekly show from Dataminded. Each episode a Dataminded engineer demos a tool or technique worth knowing about -- working code, honest takes, no hype.
Music by Aleksandr Karabanov from Pixabay
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