DP-700 Ingest and Transform Data Practice Question
Exhibit
{
"type": "Copy",
"source": {
"type": "DelimitedTextSource",
"storeSettings": {
"type": "AzureBlobFSReadSettings",
"recursive": true
}
},
"sink": {
"type": "DeltaSink",
"tableOption": "autoCreate"
}
}Refer to the exhibit. The Copy activity fails to infer the schema correctly from the source files. What is the most likely cause?
⚠ Common exam trap
Candidates often assume the Copy activity automatically detects schemas for all sinks. They fail to realize that DeltaSink specifically requires explicit schema mapping or pre-defined definitions to avoid data type defaults.
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 sink type is set to DeltaSink, which requires a pre-defined schema mapping for autoCreate.
The exhibit shows a standard copy activity without a defined dataset mapping or schema definition. When using 'autoCreate' for a Delta sink, Fabric requires a schema definition or an existing mapping to determine column types correctly. Without it, the sink assumes all data is string-based, which often leads to errors when writing to strictly typed Delta tables or results in poor query performance.
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 recursive flag is set to true, causing the sink to attempt to merge multiple schemas.
Why it's wrong here
Recursive flag simply tells the activity to look into subdirectories. It does not interfere with the initial schema inference logic itself. While recursive ingestion might lead to schema drift if files differ, it is not the primary cause of an immediate failure to infer the base schema.
- ✓
The sink type is set to DeltaSink, which requires a pre-defined schema mapping for autoCreate.
Why this is correct
Delta tables are strongly typed. When autoCreate is enabled in a copy activity, the engine needs an explicit schema definition to map the source file columns to appropriate Delta data types. Failing to provide this mapping prevents the creation of the underlying table with correct data types.
- ✗
AzureBlobFSReadSettings does not support schema inference from delimited files.
Why it's wrong here
AzureBlobFSReadSettings is fully capable of reading delimited files and performing initial column discovery. The issue is not the read capability but rather how the sink interprets the output metadata during the table creation process when moving data between different storage formats in the Fabric environment.
- ✗
The Copy activity requires an Execute Pipeline activity to initialize the sink.
Why it's wrong here
A Copy activity is sufficient on its own to move data and create tables. There is no architectural requirement for an Execute Pipeline activity to initialize a sink. Adding unnecessary layers of orchestration does not resolve underlying configuration issues related to type mapping or schema definition.
About these practice questions
This DP-700 question is part of Courseiva's 152-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This DP-700 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-700 exam.