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Analytics Everywhere #6: Semantic Layer for Machine Learning with Byron Allen

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Manage episode 342052651 series 3335894
Content provided by Preset. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Preset or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Welcome to this episode of the Analytics Everywhere podcast! In episode #6, Max chats with Byron Allen, the ML Practice Lead at Contino. In this episode, we chat about a variety of topics around the challenges of operationalizing data:

- organizational difficulties around data (data mesh vs centralized data warehouse / governance)

- what a semantic layer really is

- thin vs thick semantic layers

- entity / dataset centric modelling

- the idea of a unified semantic layer for ML and BI

- batch vs real-time ML use cases

- experimentation frameworks

- and much much more!

We hope you enjoy this episode!

Links:

Byron Allen: https://www.linkedin.com/in/byronaallen/

Byron Allen's conversation about entity centric modeling: https://youtu.be/9YcLBSqZNzE?t=2977

Drew Banin's talk at apply(): https://www.tecton.ai/apply/session-video-archive/the-dbt-semantic-layer/

Preset: https://preset.io/product

Subscribe to the podcast here: https://anchor.fm/analytics-everywhere

  continue reading

15 episodes

Artwork
iconShare
 
Manage episode 342052651 series 3335894
Content provided by Preset. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Preset or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Welcome to this episode of the Analytics Everywhere podcast! In episode #6, Max chats with Byron Allen, the ML Practice Lead at Contino. In this episode, we chat about a variety of topics around the challenges of operationalizing data:

- organizational difficulties around data (data mesh vs centralized data warehouse / governance)

- what a semantic layer really is

- thin vs thick semantic layers

- entity / dataset centric modelling

- the idea of a unified semantic layer for ML and BI

- batch vs real-time ML use cases

- experimentation frameworks

- and much much more!

We hope you enjoy this episode!

Links:

Byron Allen: https://www.linkedin.com/in/byronaallen/

Byron Allen's conversation about entity centric modeling: https://youtu.be/9YcLBSqZNzE?t=2977

Drew Banin's talk at apply(): https://www.tecton.ai/apply/session-video-archive/the-dbt-semantic-layer/

Preset: https://preset.io/product

Subscribe to the podcast here: https://anchor.fm/analytics-everywhere

  continue reading

15 episodes

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