PL-300 Visualize and analyze the data Practice Question
Exhibit
Refer to the exhibit.
```json
{
"version": "1.0",
"dataset": {
"tables": [
{
"name": "Sales",
"columns": [
{ "name": "Date", "dataType": "dateTime" },
{ "name": "Amount", "dataType": "int64" },
{ "name": "Region", "dataType": "string" }
]
}
]
}
}
```You are reviewing a Power BI dataset schema. The Date column is used in time intelligence measures. What is missing from this schema?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
There is no separate date table marked as a date table.
The correct answer is A: there is no separate date table marked as a date table. Time intelligence functions in DAX (such as TOTALYTD, SAMEPERIODLASTYEAR, and DATEADD) require a dedicated date table that is marked as a date table and has a continuous, unbroken range of dates at the day level, which a transactional fact table's Date column cannot reliably provide. Without this marked date table, the time intelligence measures will either fail or return incorrect results. Option B is irrelevant because the schema version number has no bearing on time intelligence functionality. Option C is incorrect because the Amount column's data type does not affect time intelligence calculations. Option D is incorrect because changing the Date column's data type from dateTime to date does not satisfy the requirement for a separate, marked date table.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
There is no separate date table marked as a date table.
Why this is correct
Time intelligence DAX functions, such as TOTALYTD and SAMEPERIODLASTYEAR, require a separate date table that has been marked as a date table in the model. This explicitly signals to Power BI which column holds the continuous date range, enabling proper year, quarter, month, and day filtering. Without this designated date table, time intelligence calculations will not function correctly, regardless of other model settings.
- ✗
The version should be 2.0.
Why it's wrong here
The dataset version, such as 2.0, is a metadata property that reflects the file format or compatibility level, not the semantic configuration of the model. Time intelligence behavior is determined by the presence of a marked date table and the relationships in the data model, not by version numbers. Changing the version cannot influence DAX time functions, so this is irrelevant to the reported issue.
- ✗
The Amount column should be a decimal.
Why it's wrong here
The Amount column can safely be an integer (int64) because time intelligence functions aggregate numeric values without requiring a specific data type. Whether the value is stored as decimal or integer does not affect year-over-year or month-over-month calculations. The problem lies in the missing date table, not the numeric precision of a measure column, so converting to decimal would not resolve the time intelligence failure.
- ✗
The data type for Date should be date instead of dateTime.
Why it's wrong here
A datetime data type is perfectly acceptable for a date column in Power BI, as DAX automatically truncates the time component when performing date-based operations. A date data type is not mandatory for time intelligence; what matters is having a continuous date table marked as a date table. Switching the data type to date only would not fix the core issue of no separate date table being present.
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Senior Network & Security Engineer · founder of Courseiva
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