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.<p>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):<p>[1]: <a href="https://www.youtube.com/watch?v=PFUZlNQIndo" rel="nofollow">https://www.youtube.com/watch?v=PFUZlNQIndo</a>
[2]: <a href="https://docs.malloydata.dev/documentation/" rel="nofollow">https://docs.malloydata.dev/documentation/</a>
Analytics with type-safe raw SQL (including DuckDb’s awesome extensions) is pure gold:<p><a href="https://github.com/manifold-systems/manifold/blob/master/docs/articles/duckdb_info.md" rel="nofollow">https://github.com/manifold-systems/manifold/blob/master/doc...</a>
The actual slides are linked from the intro-text:<p><a href="https://github.com/DBatUTuebingen/DiDi" rel="nofollow">https://github.com/DBatUTuebingen/DiDi</a>
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?