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Not looking for books, but rather sample datasets I can use to visualize, analyze and test if I found the right insights.
You'll find a ton of public datasets on GitHub [1].
Maven Analytics offers a monthly data analytics challenge [2] that you can enter for free. See their past competitions for some interesting datasets.
As I'm based in Ireland I'll also recommend the Irish Data Portal [3].
[1] https://github.com/awesomedata/awesome-public-datasets [2] https://mavenanalytics.io/challenges [3] https://data.gov.ie/
Superset has a great dataset with prebuilt visualization for historical video game sales if that's interesting to you
For now, we're hyperfocused on Python/Pandas/Scikit-learn as we're just getting stated (we launched in June). But we'll expand more tracks for data analytics and data engineering.
1. Think of a product that exists. Define a goal for the product and success metrics you will use. Dau, mau, user retention,incremental revenue etc. 2. Come up with gaurd rail metrics 3. Define performance and reliability metrics as well.
Now try to figure out how you would construct queries to answer these questions. And how would you visualize this info.
Then if you can find datasets or create synthetic data sets to actually write these queries or better yet create pipelines that ultimately feed a dashboard I think would be worthwhile.