- A
A. Use UploadDate as the RowKey only, but keep PartitionKey as VideoID.
Why wrong: RowKey is indexed only within a partition. With PartitionKey still set to VideoID, a query filtering on UploadDate would need to scan every partition (VideoID) to find matching dates, which is inefficient.
- B
B. Create a secondary index on UploadDate.
Why wrong: Azure Table Storage does not support secondary indexes. The only way to speed up queries is through correct PartitionKey and RowKey design.
- C
C. Change the PartitionKey to a date-based value (e.g., YYYY-MM-DD) and use VideoID as the RowKey.
By using a date as the PartitionKey, all videos uploaded on the same date are stored in the same partition. A query filtering by date can then fetch all rows from that single partition using the PartitionKey, which is extremely fast and cost-efficient.
- D
D. Migrate the data to Azure Cosmos DB Table API for better indexing.
Why wrong: Migrating to Cosmos DB is a valid option for better performance and indexing, but the question asks for a design change within Azure Table Storage to optimize queries. Option C solves the problem without migrating services.
Quick Answer
The correct choice is to change the PartitionKey to a date-based value like YYYY-MM-DD and use VideoID as the RowKey. This works because Azure Table Storage performs best when queries filter directly on the PartitionKey, enabling fast partition scans rather than expensive cross-partition lookups. By designing the partition key around the date, queries for all videos uploaded on a specific date become highly efficient, drastically reducing transaction consumption. On the DP-900 exam, this scenario tests your understanding of how partition key design directly impacts query performance and cost, often appearing as a trap where candidates mistakenly keep a unique identifier as the PartitionKey. A common memory tip is to think of the PartitionKey as your primary search filter—if you frequently query by date, make the date your PartitionKey. Remember: partition key first, row key second.
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
This DP-900 practice question tests your understanding of describe considerations for working with non-relational data on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A media company stores video metadata in Azure Table Storage. Each video has a unique VideoID, and the application frequently queries for videos uploaded on a specific date. The current table uses PartitionKey = VideoID and RowKey = UploadDate. Queries filtering by UploadDate are slow and consume many transactions. Which design change will most optimize queries that retrieve all videos from a given date?
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
C. Change the PartitionKey to a date-based value (e.g., YYYY-MM-DD) and use VideoID as the RowKey.
Option C is correct because Azure Table Storage queries are most efficient when the PartitionKey is used as the primary filter. By changing the PartitionKey to a date-based value (e.g., YYYY-MM-DD), queries for all videos uploaded on a specific date become partition scans, which are fast and consume minimal transactions. Using VideoID as the RowKey still allows unique identification of each video within that date partition.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A. Use UploadDate as the RowKey only, but keep PartitionKey as VideoID.
Why it's wrong here
RowKey is indexed only within a partition. With PartitionKey still set to VideoID, a query filtering on UploadDate would need to scan every partition (VideoID) to find matching dates, which is inefficient.
- ✗
B. Create a secondary index on UploadDate.
Why it's wrong here
Azure Table Storage does not support secondary indexes. The only way to speed up queries is through correct PartitionKey and RowKey design.
- ✓
C. Change the PartitionKey to a date-based value (e.g., YYYY-MM-DD) and use VideoID as the RowKey.
Why this is correct
By using a date as the PartitionKey, all videos uploaded on the same date are stored in the same partition. A query filtering by date can then fetch all rows from that single partition using the PartitionKey, which is extremely fast and cost-efficient.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
D. Migrate the data to Azure Cosmos DB Table API for better indexing.
Why it's wrong here
Migrating to Cosmos DB is a valid option for better performance and indexing, but the question asks for a design change within Azure Table Storage to optimize queries. Option C solves the problem without migrating services.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume secondary indexes (like in SQL databases) exist in Azure Table Storage, or they think changing RowKey alone is sufficient, failing to realize that PartitionKey is the only partition-level filter and must align with the query pattern.
Detailed technical explanation
How to think about this question
Azure Table Storage uses a clustered index on (PartitionKey, RowKey), and queries that specify PartitionKey are served from a single partition, achieving O(1) lookup. Without PartitionKey in the filter, the service must scan all partitions, which scales linearly with the number of partitions. In real-world scenarios, this design pattern is critical for time-series data where date-based partitioning enables efficient range queries and throttling avoidance.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe considerations for working with non-relational data on Azure — This question tests Describe considerations for working with non-relational data on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: C. Change the PartitionKey to a date-based value (e.g., YYYY-MM-DD) and use VideoID as the RowKey. — Option C is correct because Azure Table Storage queries are most efficient when the PartitionKey is used as the primary filter. By changing the PartitionKey to a date-based value (e.g., YYYY-MM-DD), queries for all videos uploaded on a specific date become partition scans, which are fast and consume minimal transactions. Using VideoID as the RowKey still allows unique identification of each video within that date partition.
What should I do if I get this DP-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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