DP-203 Develop data processing Practice Question
You are designing a data processing pipeline that ingests data from a REST API endpoint every hour. The API returns JSON data with a varying schema. You need to store the raw data in Azure Data Lake Storage Gen2 and later process it using Azure Databricks. Which file format should you use for the raw data storage?
⚠ Common exam trap
Watch out — candidates often choose Parquet or Avro for their performance benefits, forgetting that raw data ingestion with varying schemas must prioritize schema flexibility over query optimization, which JSON uniquely provides.
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
✓
JSON
C is correct because the raw data arrives from a REST API with a varying JSON schema, and storing it in JSON format preserves the exact structure and schema variability without data loss or transformation. JSON is schema-on-read, meaning the raw data can be ingested as-is into Azure Data Lake Storage Gen2 and later processed by Azure Databricks, which natively supports JSON parsing. This avoids premature schema enforcement that would occur with columnar or binary formats.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Parquet
Why it's wrong here
Requires schema definition; not ideal for varying schema.
- ✗
CSV
Why it's wrong here
Cannot represent nested structures well.
- ✓
JSON
Why this is correct
Preserves schema flexibility and is easy to store.
- ✗
Avro
Why it's wrong here
More suited for serialization, not raw storage.
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