Q: 14
You plan to deploy an Azure Databricks Data Science & Engineering workspace and ingest data into
the workspace.
Where should you persist the ingested data?
Options
Discussion
If they said the data was already highly structured or transaction-based, C (Azure SQL) might be an edge case. But with Databricks, unless the scenario specifies only relational needs, B is the usual pick since Data Lake handles raw and semi-structured data at scale. Seems pretty clear unless another requirement is hidden.
C or B? I get why some said A since Azure Files can be mounted, but for Databricks workloads at scale Azure Data Lake (B) is usually recommended. Azure SQL (C) is tempting if it was only structured data, but that’s not typical for raw ingestion.
A tbh. Azure Files can be used for storing ingested data and is supported by Databricks mounts, so it seemed like a valid pick for raw datasets too. Maybe missing something but I could see cases for A as well.
B, If the data is raw and needs to be scalable for analytics, Data Lake fits best. Using Azure SQL or Cosmos would be more for processed/structured sets. Pretty sure this matches what I've seen in similar exam reports.
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