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Over the past year, I've found myself turning to ChatGPT more frequently than Google for "research". I have some observation after that time: my knowledge retention and acquisition seem to have improved, and that too without any noticeable extra effort. A little bit like being back at school were it was required to make notes from multiple subjects which led to (at least for me) having far more at-hand diverse knowledge available.

I'm beginning to think this might be because interacting with ChatGPT constantly prompts to articulate thoughts in writing. A lot. There have been instances where just typing out my question has led me to the answer. This experience makes me wonder if it's akin to those studies pointing out that writing with pen and paper enhances memory retention but realized here in the context of chatting with LLM. Before that, neither Google, online board posting or personal chatting didn't actually have a similar effect because of "intensity" difference.

I am designing a data-intensive web application. Because I am not exactly a full stack engineer I catch myself often re-modeling data schema I decided on as the work progresses. This effectively costs me a lot of time and back-and-forth in the project. I have a feeling it can be a more organized process than just rules of thumb all the way.

I am dealing with mixed data types. On one hand I need key-value structure, on the other hand, I need it to hold references to the filesystem/files directories. All of data comes well-structured but it can often be of considerable size.

Question is, what are good resources, case studies or personal blog posts in the area of building a data-intensive app. I am looking specifically for the resources on deciding how to organize data for storage and future retrieval/transformation in context of smaller/medium size architectures (ie. iCloud case study is of little use to me most probably)