DP-203 Design and implement data storage Practice Question
Your organization uses Azure Synapse Analytics dedicated SQL pool. You need to implement a solution that reduces storage costs for historical data that is rarely accessed but must be available for querying within minutes. The solution should not require application changes. What should you do?
⚠ Common exam trap
It's easy for candidates to confuse PolyBase with external tables, assuming PolyBase requires data to be in hot tier or that lifecycle management alone solves the query latency requirement, but they overlook the rehydration delay of archive tier and the need for zero application changes.
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
✓
Create external tables pointing to data stored in Azure Data Lake Storage Gen2 with appropriate tiering
Creating external tables in Azure Synapse Analytics dedicated SQL pool that point to data stored in Azure Data Lake Storage Gen2 (ADLS Gen2) allows you to query historical data directly from low-cost storage tiers (e.g., cool or archive) without moving it into the pool. This reduces storage costs for rarely accessed data while keeping it queryable within minutes, and requires no application changes since the external tables are accessed via standard T-SQL queries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create external tables pointing to data stored in Azure Data Lake Storage Gen2 with appropriate tiering
Why this is correct
External tables allow querying data in Data Lake Storage without moving it, and tiering reduces cost.
- ✗
Use Azure Blob Storage with PolyBase and configure lifecycle management to archive data
Why it's wrong here
This is similar but Data Lake Storage is more integrated with Synapse; however, this could work but requires more configuration.
- ✗
Drop older partitions and reload data when needed
Why it's wrong here
Dropping partitions permanently deletes data; reloading requires changes and time.
- ✗
Change the distribution to round-robin for the fact table
Why it's wrong here
Distribution affects query performance, not storage costs.
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