When I think about choosing between data warehouses and data lakes for university database models, there are a few important things to consider.

Here are some key points:

1. Data Structure:

   • Data warehouses work best with structured data. This means they are really good for complex questions and analysis.
   • Data lakes can handle unstructured data. This gives you more options, but they might be slower when you want to pull out specific information.

2. Query Performance:

   • If you need fast answers to your questions, a data warehouse is the better choice. It’s built for tasks that require reading data, which makes it perfect for creating reports.
   • Data lakes can be slower because they deal with different types of data. You might need to reshape the data before you can use it.

3. Scalability:

   • Data lakes can grow easily and handle huge amounts of different kinds of data.
   • However, as the amount of data increases, keeping everything running quickly might need extra attention.

In short, if you want quick results from organized data, choose a data warehouse. But if you need more flexibility and are working with bigger data sets, a data lake could be the better option.