Free Microsoft Data Engineering DP-700 Actual Exam Questions - Question 13 Discussion
HOTSPOT You are building a data loading pattern for Fabric notebook workloads. You have the following code segment: 
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. 
I also think the batch processing angle is strong here since checkpointing usually isn’t part of streaming setups. Plus, the code doesn’t show any triggers or listeners that’d indicate real-time data flow, so No for streaming feels right. On schema updates, there’s no explicit handling in the snippet, so that’s another No from me. The focus seems more on loading and saving states rather than evolving schemas or real-time ingestion.
I’m saying No for real-time streaming because the code looks like it’s designed for batch uploads with checkpoints, not continuous data streams. Also, No on automatic schema evolution since there’s no schema update logic shown.
The code snippet doesn’t show any explicit error handling or retries, so I’d say No on automatic failure recovery. Also, since it’s a notebook pattern, it’s likely designed for batch loads rather than streaming data, so No on continuous streaming.
I’m saying Yes for incremental loads because the code snippet uses a merge strategy, which usually supports loading only changed data instead of full reloads. That seems more efficient here.
I think the answer for parallel loading is Yes since the code uses the COPY command which is designed for parallel data loads. That should speed up ingest compared to single-threaded methods.
I’d say No for pre-processing too because the code shows built-in connectors that simplify loading. The schema and data validation look handled by the connector, so no manual pre-processing needed.
No for pre-processing; connectors handle that automatically.
Honestly, I don’t think pre-processing is required in this specific pattern because the code uses built-in connectors that handle schema inference and data typing. So, the data source can usually be loaded directly unless there are specific formatting issues. Also, the statements about using Synapse Analytics and Delta Lake seem off since the code snippet focuses on Power BI Fabric notebook workflows, which are more integrated with Azure Data Lake Storage and Fabric's own data pipelines. I’d mark “No” for anything mentioning external pre-processing or unsupported storage types here.
Can anyone confirm if the data source needs to be pre-processed before loading here?