Your question is Normalization in Trade Data Models. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
When you build relational datasets for trading, reference, or reporting workflows, table design affects query correctness just as much as SQL syntax. A poorly structured schema can create duplicate data, inconsistent updates, and harder downstream analysis.
Explain what data normalization means in a relational database. You should describe the goal of normalization, the main idea behind common normal forms, and why normalization is important for preserving data integrity when storing entities such as traders, accounts, instruments, and executions.
Keep your answer practical and interview-focused. You do not need to recite every formal rule in depth, but you should be able to explain how normalization reduces redundancy, prevents insert/update/delete anomalies, and supports many-to-one relationships through keys and separate tables. It is also useful to mention when a team might intentionally denormalize for analytics or performance.