- A
Use INSERT statements to add rows incrementally
Why wrong: INSERT statements are slow for large volumes and cause high transaction log activity and locking, degrading concurrent query performance.
- B
Use CREATE TABLE AS SELECT (CTAS) to build a new table and rename it
Why wrong: CTAS avoids locking issues but the rename operation can cause brief unavailability and may block queries for the duration of the rename.
- C
Load data into a staging table, then use partition switching to swap the latest partition
Partition switching is a fast, metadata-only operation that adds new data without blocking concurrent reads, ideal for large daily loads.
- D
Use PolyBase to load data directly into the fact table
Why wrong: PolyBase loading directly into the fact table can cause fragmentation, locking, and index maintenance overhead, impacting query performance.
Quick Answer
The correct answer is to load data into a staging table, then use partition switching to swap the latest partition. This strategy optimizes both load speed and query performance because partition switching in Azure Synapse Analytics dedicated SQL pool is a metadata-only operation—when you run ALTER TABLE SWITCH, the system instantly reassigns the partition boundaries without physically moving the 500 GB of data, allowing concurrent reads on the most recent data to proceed without blocking or degradation. On the DP-900 exam, this scenario tests your understanding of how to balance data ingestion with query concurrency, often appearing as a case study where a trap answer suggests direct inserts or index rebuilds, which would cause locking and performance hits. Remember the key insight: partition switching is like swapping a book on a shelf—you change the label, not the book itself. For the exam, think “switch, don’t move” to recall that metadata swaps keep queries running smoothly.
DP-900 Describe an analytics workload on Azure Practice Question
This DP-900 practice question tests your understanding of describe an analytics workload 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. A key principle to apply: partition switching is a metadata-only operation, making it extremely fast.. 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 company uses Azure Synapse Analytics dedicated SQL pool to store a large fact table containing 5 TB of sales transactions. New data arrives continuously and is loaded daily. The company needs to load 500 GB of new data each day while allowing concurrent read queries on the most recent data without performance degradation. Which loading strategy optimizes both load speed and query performance?
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
Load data into a staging table, then use partition switching to swap the latest partition
Option C is correct because partition switching allows you to load new data into a staging table, then instantly swap the staging partition with the target table's latest partition using ALTER TABLE SWITCH. This minimizes metadata changes and avoids data movement, enabling fast loads while keeping the fact table online for concurrent read queries without blocking or performance degradation.
Key principle: Partition switching is a metadata-only operation, making it extremely fast.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use INSERT statements to add rows incrementally
Why it's wrong here
INSERT statements are slow for large volumes and cause high transaction log activity and locking, degrading concurrent query performance.
- ✗
Use CREATE TABLE AS SELECT (CTAS) to build a new table and rename it
Why it's wrong here
CTAS avoids locking issues but the rename operation can cause brief unavailability and may block queries for the duration of the rename.
- ✓
Load data into a staging table, then use partition switching to swap the latest partition
Why this is correct
Partition switching is a fast, metadata-only operation that adds new data without blocking concurrent reads, ideal for large daily loads.
Related concept
Partition switching is a metadata-only operation, making it extremely fast.
- ✗
Use PolyBase to load data directly into the fact table
Why it's wrong here
PolyBase loading directly into the fact table can cause fragmentation, locking, and index maintenance overhead, impacting query performance.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose PolyBase (Option D) because it is associated with fast data loading, but they overlook that direct loading into a large fact table causes fragmentation and locking, whereas partition switching provides both speed and query isolation.
Detailed technical explanation
How to think about this question
Partition switching in Azure Synapse dedicated SQL pool uses the ALTER TABLE SWITCH statement to move a partition's data between tables at the metadata level, completing in seconds regardless of data size. The staging table must have the same schema and partition boundary as the target partition, and the switch is a transactionally consistent operation that does not block concurrent reads. In real-world scenarios, this pattern is critical for maintaining SLAs on large fact tables where daily loads exceed 100 GB and query concurrency is high.
KKey Concepts to Remember
- Partition switching is a metadata-only operation, making it extremely fast.
- It allows new data to be loaded into a staging table without impacting the main table.
- Partition switching minimizes locking and ensures high availability for read queries.
- The staging table must have an identical schema and partitioning scheme to the target table.
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
Partition switching is a metadata-only operation, making it extremely fast.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Partition switching is a metadata-only operation, making it extremely fast. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review partition switching is a metadata-only operation, making it extremely fast., then practise related DP-900 questions on the same topic to reinforce the concept.
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Describe an analytics workload on Azure — study guide chapter
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Partition switching is a metadata-only operation, making it extremely fast..
What is the correct answer to this question?
The correct answer is: Load data into a staging table, then use partition switching to swap the latest partition — Option C is correct because partition switching allows you to load new data into a staging table, then instantly swap the staging partition with the target table's latest partition using ALTER TABLE SWITCH. This minimizes metadata changes and avoids data movement, enabling fast loads while keeping the fact table online for concurrent read queries without blocking or performance degradation.
What should I do if I get this DP-900 question wrong?
Review partition switching is a metadata-only operation, making it extremely fast., then practise related DP-900 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Partition switching is a metadata-only operation, making it extremely fast.
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Last reviewed: Jun 11, 2026
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