DP-203 Design and implement data storage Practice Question
A multinational bank needs to store customer transaction records for 10 years to meet regulatory compliance. The data is rarely accessed after the first year. The solution must minimize storage costs while allowing queries on recent data with low latency. Which tiering strategy should you implement?
⚠ Common exam trap
Many candidates choose Option C thinking TTL in Cosmos DB can handle retention, but TTL deletes data automatically, which violates regulatory retention requirements, not just cost optimization.
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
✓
Use Azure Blob Storage with lifecycle management to transition from Hot to Cool to Archive tiers
Azure Blob Storage lifecycle management automatically transitions blobs from Hot to Cool to Archive tiers based on age, minimizing storage costs for rarely accessed data after the first year while keeping recent data in Hot tier for low-latency queries. This aligns with the 10-year retention requirement and cost optimization goal without manual intervention.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Store all data in Azure SQL Database with partitioning and drop older partitions
Why it's wrong here
Partition dropping deletes records permanently, breaching the 10-year retention mandate, and Azure SQL Database storage costs stay high for cold data. It suits active datasets where old partitions are genuinely disposable, not regulatory archives needing cheap long-term retention with fast recent queries.
- ✗
Use Azure Data Lake Storage Gen2 with a single storage tier
Why it's wrong here
A single tier keeps all ten years on hot storage, so cost reduction for rarely accessed records never happens. Tiering (hot for year one, archive beyond) is required. A single tier suits datasets accessed uniformly, or short-lived data where lifecycle transitions add no benefit.
- ✗
Store data in Azure Cosmos DB with time-to-live (TTL) and use Azure Blob Storage for backups
Why it's wrong here
Cosmos DB TTL deletes records automatically once they expire, so ten-year retention cannot be met, and it is a transactional store rather than an archival tier. It is tempting because TTL suits session data and caches where automatic expiry is genuinely desirable.
- ✓
Use Azure Blob Storage with lifecycle management to transition from Hot to Cool to Archive tiers
Why this is correct
Lifecycle management rules automatically demote blobs from Hot to Cool after 30 days, then to Archive, satisfying the 10-year retention at lowest cost. Hot tier keeps recent data queryable with low latency, while Archive stores rarely accessed records offline, meeting the regulatory constraint.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.