Data Granularity Quiz

What you'll be asked

1. What does the term 'data granularity' refer to in the context of data modeling?
2. If you are designing a sales reporting model, which of the following represents the highest level of granularity?
3. Why is it generally recommended to keep fact tables at the lowest possible grain during the initial modeling phase?
4. You notice your model is performing slowly because users are performing complex calculations on millions of rows of atomic data. What is an appropriate optimization strategy regarding granularity?
5. Consider a scenario where you have a 'Sales' fact table at the transaction level and a 'Budget' table at the monthly product category level. How should you handle the granularity mismatch when building a report that compares Sales vs Budget?

Answers and explanations come after you submit.