Describe considerations for working with non-relational data on Azure →mediumMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
A company stores IoT sensor data in Azure Blob Storage. The data is written hourly and must be retained for 90 days. After 90 days, it must be automatically deleted. Which access tier should be used for cost optimization during the retention period?
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
✓
Cool tier
The Cool tier is optimized for data that is infrequently accessed and stored for at least 30 days, with lower storage costs and higher access costs. Hot tier is for frequent access and would be more expensive. Archive tier has a 180-day minimum retention penalty. Premium tier is for high transaction volumes and is not cost-effective for this scenario.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Premium tier
Why it's wrong here
The Premium tier in Azure Blob Storage is a performance-tier offering, not a cost-optimized access tier, designed for low-latency and high-throughput workloads such as real-time analytics or interactive applications. IoT sensor data written hourly and retained for 90 days does not require sub-millisecond response times or dedicated performance features, so adopting Premium would dramatically inflate storage costs without delivering relevant benefits. Since the workload is batch ingestion and infrequent reads, the Premium tier is an over-engineered and cost-prohibitive choice.
- ✗
Archive tier
Why it's wrong here
Archive access tier provides the lowest storage price, but it enforces a 180-day minimum retention period and charges an early-deletion penalty if data is removed or moved before that threshold. With a required retention period of only 90 days, deploying sensor logs to Archive would trigger a penalty for every blob deleted at the 90-day mark, erasing the storage savings. Furthermore, Archive’s multi-hour rehydration time to access data is unnecessary and impractical for a dataset that may need occasional analytical queries within a short time window.
- ✓
Cool tier
Why this is correct
Cool access tier is specifically designed for data that is infrequently accessed and retained for at least 30 days, offering a lower storage price than Hot while keeping millisecond latency for reads. Hourly IoT sensor logs that remain unread for the majority of their 90-day lifecycle align perfectly with Cool's cost profile, and the 90-day retention safely exceeds the 30-day minimum without imposing any early-deletion fees. It also allows immediate access for on-demand analysis, making it the most balanced and technically appropriate choice for this scenario.
- ✗
Hot tier
Why it's wrong here
Hot access tier is optimized for data that is accessed frequently, with higher storage costs but lower transaction costs than other tiers. IoT sensor data written hourly but rarely read during its 90-day retention would sit idle, meaning the storage-cost premium provides no operational value. Given that the workload is predominantly writes with occasional reads, Hot's low-latency advantages do not justify the higher monthly storage expense, making it a cost-inefficient alternative to Cool.
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
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Blob storage
Blob storage is a cloud service for storing large amounts of unstructured data, such as text or binary data, like documents, images, and videos.
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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