DP-203 Certification Practice Question #34

Question

You are implementing a batch dataset in the Parquet format.
Data files will be produced be using Azure Data Factory and stored in Azure Data Lake Storage Gen2. The files will be consumed by an Azure Synapse Analytics serverless SQL pool.
You need to minimize storage costs for the solution.
What should you do?

Accepted Answer

The only option that directly reduces the storage footprint of the Parquet files stored in ADLS Gen2 is compressing them. Microsoft documentation for Parquet-based Azure data workloads consistently uses and recommends Snappy as a supported, efficient compression codec for analytical data. By contrast, `OPENROWSET` and external tables change access patterns rather than the bytes stored in the source files, and storing all values as strings would usually waste space. The question asks how to minimize storage costs for the dataset, so choosing compression is the most direct and defensible answer.

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