I would focus on theory first, then tools. I recommend the following, in order: 1) Data modeling: Fully read Kimball's book, The Data Warehouse Toolkit, 3rd ed

I would focus on theory first, then tools. I recommend the following, in order: 1) Data modeling: Fully read Kimball's book, The Data Warehouse Toolkit, 3rd edition. It's outdated and boring but it's an excellent foundation, so don't skip it. 2) Data modeling: After #1 above, spend at least 30 minutes learning about Inmon's approach, the ER Model, 3NF, etc. You can find some decent YouTube videos. You don't need to learn this deeply, but you should understand how it's different than Kimball's approach. 3) Data warehousing & data lakes: Read the academic paper titled "Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics." For an academic paper, it's surprisingly approachable. 4) If you don't know this already, do 15 minutes of googling to understand ETL vs ELT and the pros and cons of each approach. 5) Putting it all together: Once you've done the things above, then read Kleppman's book, Designing Data-Intensive Applications. 6) Focus on the future: Spend a little time learning about streaming architectures, including batch/microbatch/streaming and pros and cons for each. You may also want to learn about some of the popular tools, but you can easily google those.