If you are a data scientist or do anything with data... duckdb is like a swiss army knife. So many great ways it can help your workflow. The original video from CMU in 2020 [1] is a classic. Minutes 3-8 present a good argument for adding duckdb to your data cleaning/processing workflow.
And if you want to add a semantic layer on top of data, Malloy [2] is my favorite so far (it has duckdb built in):
If you are a data scientist or do anything with data... duckdb is like a swiss army knife. So many great ways it can help your workflow. The original video from CMU in 2020 [1] is a classic. Minutes 3-8 present a good argument for adding duckdb to your data cleaning/processing workflow.
And if you want to add a semantic layer on top of data, Malloy [2] is my favorite so far (it has duckdb built in):
[1]: https://www.youtube.com/watch?v=PFUZlNQIndo [2]: https://docs.malloydata.dev/documentation/
Analytics with type-safe raw SQL (including DuckDb’s awesome extensions) is pure gold:
https://github.com/manifold-systems/manifold/blob/master/doc...
The actual slides are linked from the intro-text:
https://github.com/DBatUTuebingen/DiDi
Unfortunately it does not seem that there are lecture videos.
thank you! Learned why DuckDB is named this way
Am I missing something or is the content empty?
https://github.com/DBatUTuebingen/DiDi
Thank you, I didn't realize all of the course counted as "slides and auxiliary material" haha
edit: Really great stuff in here. Every day at work I think about how much I love DuckDB