1Z0-1041-20 · Question #56
Which two elements does a well modeled Fact Table consist of?
The correct answer is A. Dimension Keys D. Measures. Explanation/Reference: https://docs.oracle.com/cd/E05553_01/books/admintool/admintool_DataModeling8.html
Question
Which two elements does a well modeled Fact Table consist of?
Options
- ADimension Keys
- BREST APIs
- DMeasures
How the community answered
(59 responses)- A78% (46)
- B22% (13)
Explanation
Explanation/Reference: https://docs.oracle.com/cd/E05553_01/books/admintool/admintool_DataModeling8.html
Topics
Community Discussion
4
Mateus R.Jun 27, 2026A Fact Table is like a receipt at a store: the receipt has line items with dollar amounts (those are your Measures, option D) and it also has little codes on it pointing to the store location, the cashier, the date (those are your Dimension Keys, option A) so you can look up all the context later. REST APIs (option B) are a networking concept that has nothing to do with how you structure a data warehouse table, so toss that one out.
Ola B.Jun 29, 2026The receipt analogy is solid, and I will add one thing to lock it in: go spin up a quick star schema in something like DBeaver or even a free BigQuery sandbox and you will physically see how those foreign keys in the Fact Table join back to Dimension Tables, which makes the whole "codes pointing elsewhere" idea click faster than any analogy.
Ola B.Jun 27, 2026I actually flagged this one during my exam and came back to it, because REST APIs sitting in the options felt like a trap they knew people would second-guess themselves on. Once I pictured the fact table I had built in an Oracle Analytics Cloud lab, with my dimension keys joining out to the dimension tables and my numeric measures sitting right there in the middle, A and D were the only ones that made any sense.
Nadia M.Jun 27, 2026Good catch on this one, A and D are the right call since a fact table lives and dies by its foreign keys back to dimensions and the numeric measures you actually analyze. Quick question though, when you have something like a factless fact table, you technically have dimension keys but no real measures, so how do you think about that edge case when the exam asks you to identify fact table "elements"?