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Advances in ML have transformed data privacy from a regulatory necessity into an opportunity to improve the work of data people.
Synthetic data for modeling + testing is one example of a hard thing that's now easy - and in this conversation with Tristan and Julia, Ian + Abhishek cover many other ways that privacy can actually be a skill that propels your work forward, rather than a mere legal best practice.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.
By dbt Labs, Inc.4.7
2929 ratings
Advances in ML have transformed data privacy from a regulatory necessity into an opportunity to improve the work of data people.
Synthetic data for modeling + testing is one example of a hard thing that's now easy - and in this conversation with Tristan and Julia, Ian + Abhishek cover many other ways that privacy can actually be a skill that propels your work forward, rather than a mere legal best practice.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.

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