Q1. In this hospital dataset, which of the following is a fact table?
Type: Multiple Choice
- doctors
- patients
- appointments
- None of the tables are fact tables
Correct Answer: appointments
Why: appointments (along with treatments and billing) records transactional events that happen repeatedly and reference other tables — the hallmark of a fact table. patients and doctors are dimension tables: they describe “who,” not “what happened.”
Q2. A many-to-many relationship between two tables is generally something you should actively avoid unless there’s a specific reason for it, because it can cause ambiguous or incorrect filtering.
Type: True/False
Correct Answer: True
Why: Many-to-many relationships make it unclear how filters should flow between tables, which can lead to double-counted or inconsistent totals. The recommended pattern is one-to-many relationships flowing from dimension tables into fact tables.
Q3. What does “cross-filter direction” control in a Power BI relationship?
Type: Short Answer
Correct Answer: It controls which direction filters propagate across a relationship — single direction (from the “one” side to the “many” side) or bidirectional (both ways).
Why: Cross-filter direction determines whether selecting a value in one table (e.g., a doctor) filters the connected table (e.g., appointments), and whether that filtering can also flow back the other way. Single direction is the default and generally recommended setting because it keeps filter behavior predictable.
Q4. Why would you add a standalone Date dimension table to this hospital model instead of just using appointment_date, bill_date, and treatment_date directly?
Type: Multiple Choice
- Power BI requires at least one table with no relationships
- A single Date table lets one date slicer filter appointments, treatments, and billing simultaneously, and enables consistent time intelligence
- It reduces the file size of the .pbix
- Date columns cannot be used in visuals unless they come from a dedicated Date table
Correct Answer: A single Date table lets one date slicer filter appointments, treatments, and billing simultaneously, and enables consistent time intelligence
Why: Without a shared Date table, each fact table’s date column is filtered independently, so a single slicer can’t control all three at once. A dedicated Date table connected to each date column gives you one consistent way to filter and enables accurate time-intelligence DAX, such as month-over-month trends.