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The Hard Problems™️ of Data Observability w/ Kevin Hu of Metaplane

The Hard Problems™️ of Data Observability w/ Kevin Hu of Metaplane

FromThe Analytics Engineering Podcast


The Hard Problems™️ of Data Observability w/ Kevin Hu of Metaplane

FromThe Analytics Engineering Podcast

ratings:
Length:
43 minutes
Released:
Apr 8, 2022
Format:
Podcast episode

Description

As a PhD candidate at MIT, Kevin (and friends) published Sherlock, a data type detection engine (a surprisingly bedeviling problem) for data cleaning + data discovery. Now as co-founder and CEO of Metaplane, a data observability startup, Kevin applies these same automated data discovery methods to help data teams keep their data healthy. In this conversation with Tristan & Julia, Kevin wins the coveted award for “most crystal-clear explanations of complex technical concepts through physics analogy.”   For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
Released:
Apr 8, 2022
Format:
Podcast episode

Titles in the series (59)

Tristan Handy has been curating the Analytics Engineering Roundup newsletter since 2015, pulling together the internet’s best data science & analytics articles. Tristan and co-host Julia Schottenstein now bring the Roundup to real life, hosting biweekly conversations with data practitioners inventing the future of analytics engineering. You can view full episode summaries and read back issues of the Roundup newsletter at https://roundup.getdbt.com. The podcast is sponsored by dbt labs, makers of the data transformation framework dbt. To reach our team, drop a note to podcast@dbtlabs.com.