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. 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.
You are the data engineer for a large retail company. The company has an existing on-premises SQL Server database with 10 years of transactional data. They want to move this data to Azure to enable advanced analytics using Azure Synapse Analytics. The data includes customer orders, product details, and inventory. The solution must minimize data movement and support both batch and real-time analytics. The company also wants to use Power BI for reporting. They have a limited budget and prefer a serverless option for compute. You are evaluating the following approaches: A) Use Azure Data Factory to copy all data to Azure Data Lake Storage Gen2, then use Azure Synapse Serverless SQL pool to query the data, and finally connect Power BI to the serverless SQL endpoint. B) Use Azure Database Migration Service to migrate the SQL Server database to Azure SQL Database, then use Azure Synapse Analytics with a dedicated SQL pool to perform analytics, and connect Power BI to the dedicated pool. C) Use Azure Data Factory to copy all data to Azure Blob Storage, then use Azure Stream Analytics to perform real-time analytics, and connect Power BI directly to Stream Analytics output. D) Use Azure Data Factory to copy historical data to Azure Data Lake Storage Gen2, use Azure Synapse Serverless SQL pool for batch analytics, and use Azure Event Hubs and Stream Analytics for real-time data, with Power BI connecting to both serverless SQL and Stream Analytics. Which approach best meets the requirements?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Option A
Why wrong: Missing real-time analytics capability.
Option C
Why wrong: Blob Storage is not optimal for analytics; Stream Analytics not ideal for batch.
Option B
Why wrong: Uses dedicated SQL pool (not serverless) and lacks real-time.
Option D
Combines serverless batch and real-time, minimizes data movement, and uses Power BI.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Option D
Option D best meets the requirements because it uses Azure Data Factory to copy historical data to Azure Data Lake Storage Gen2, enabling cost-effective storage and batch analytics via Azure Synapse Serverless SQL pool (serverless compute). It also incorporates Azure Event Hubs and Stream Analytics for real-time data ingestion and analytics, with Power BI connecting to both the serverless SQL endpoint and Stream Analytics output. This minimizes data movement by keeping data in the lake, supports both batch and real-time analytics, and uses a serverless option to stay within a limited budget.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Option A
Why it's wrong here
Missing real-time analytics capability.
Option C
Why it's wrong here
Blob Storage is not optimal for analytics; Stream Analytics not ideal for batch.
Option B
Why it's wrong here
Uses dedicated SQL pool (not serverless) and lacks real-time.
Option D
Why this is correct
Combines serverless batch and real-time, minimizes data movement, and uses Power BI.
Clue confirmation
The clue words "best", "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often choose Option A because it uses serverless SQL and Power BI, but they overlook the explicit requirement for real-time analytics, which Option A does not address.
Detailed technical explanation
Azure Synapse Serverless SQL pool queries data directly from Data Lake Storage Gen2 using T-SQL, leveraging a pay-per-query model that aligns with a limited budget. Azure Event Hubs can ingest millions of events per second, and Stream Analytics can perform windowed aggregations in real-time, outputting to Power BI via the Power BI output adapter. The combination allows a single data lake to serve both batch and real-time workloads without duplicating data, which is a key principle of a modern data architecture.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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FAQ
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
The correct answer is: Option D — Option D best meets the requirements because it uses Azure Data Factory to copy historical data to Azure Data Lake Storage Gen2, enabling cost-effective storage and batch analytics via Azure Synapse Serverless SQL pool (serverless compute). It also incorporates Azure Event Hubs and Stream Analytics for real-time data ingestion and analytics, with Power BI connecting to both the serverless SQL endpoint and Stream Analytics output. This minimizes data movement by keeping data in the lake, supports both batch and real-time analytics, and uses a serverless option to stay within a limited budget.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "best", "minimum / minimize". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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