jason's honest review, DBT with a Silicon Valley Engineer course
Reviews 34
Average rating 5
I am watching this after your Airflow lecture. I believe this is the only lecture available on information system modeling. I will certainly purchase your "Standard of Data Architecture" lecture later, as it's something you must know to get promoted. As a junior engineer who practically lives on Inflearn, I would be willing to spend hundreds of dollars on well-made, toy project-style ELT practice examplesโwhere you take APIs and various raw data, put them into ODS, and combine them into fact and dimension tables to go from DW to DM. However, I haven't been able to find anything like that... ใ Do you happen to have any plans to launch something related to this in the future? ใ
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Hello Taekyung Hong, Thank you for your kind words. ๐ I also had many similar thoughts while creating the lectures. As you mentioned, the most regrettable part of learning dbt or data modeling is that there aren't many practice environments where you can go beyond simply learning syntax or features and actually design and build from ODS โ DW โ DM using data at a scale similar to real-world business. Especially from a data engineer's perspective, the experience of collecting data from APIs, logs, and operational databases, performing Fact/Dimension modeling using dbt, and finally creating a data mart is much closer to actual practical skills. However, it is surprisingly difficult to find educational content in this format. While I don't have a specific lecture in preparation at the moment, I agree that a practice-oriented data warehouse construction project, as you suggested, is highly valuable. If I plan a lecture in the future, I will consider a format where students can experience the flow of building an actual data platform, going beyond simple explanations of dbt features. Thank you for sharing your great opinion. This kind of feedback is a huge help in preparing for the next lecture. ๐
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Wow, thank you so much for responding to a junior's low-level question. Even if it doesn't necessarily involve dbt, a simple practice session pulling data via DB-to-DB procedures would be a huge help. Rather than just focusing on tech stacks like Spark or Airflow, I want to learn the ELT/ETL philosophy of a senior data engineerโthings like the criteria for dividing Fact and Dimension tables in information system modeling, ensuring idempotence before loading data, and other critical factors to consider in various situations.
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