DP-203 Develop data processing Practice Question
Exhibit
{
"dataflows": [
{
"name": "TransformSales",
"properties": {
"sources": [
{
"name": "SalesSource",
"dataset": {
"referenceName": "SalesDataset",
"type": "DatasetReference"
}
}
],
"transformations": [
{
"name": "AggregateSales",
"type": "Aggregate",
"inputs": ["SalesSource"],
"aggregates": [
{
"column": "TotalAmount",
"function": "SUM",
"input": "Amount"
}
]
}
],
"sink": {
"name": "SalesSink",
"dataset": {
"referenceName": "AggregatedSalesDataset",
"type": "DatasetReference"
}
}
}
}
]
}Refer to the exhibit. You have a mapping data flow in Azure Data Factory that aggregates sales data. The data flow runs successfully but the sink table contains only the total sum per run instead of per product. What is missing?
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
✓
The aggregate transformation does not have a groupBy column
The aggregate transformation must include a groupBy column (e.g., ProductID) to produce per-product totals. Without a groupBy, the aggregate sums all rows into a single total per run. Option A is incorrect because filtering by date would not fix the lack of grouping. Option C is incorrect because a filter transformation is unrelated to aggregation grouping. Option D is incorrect because the sink append mode does not affect the aggregation logic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The source dataset is not filtering by date
Why it's wrong here
Not relevant.
- ✓
The aggregate transformation does not have a groupBy column
Why this is correct
Without groupBy, it aggregates all rows.
- ✗
The data flow is missing a filter transformation
Why it's wrong here
Not needed.
- ✗
The sink dataset is not configured to append
Why it's wrong here
Append vs replace doesn't fix aggregation.
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