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: azure Synapse Analytics unifies data warehousing, big data analytics, and data integration.. 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 manufacturing company ingests a continuous stream of sensor data from thousands of IoT devices into Azure Event Hubs. The company also stores historical equipment maintenance records in Azure SQL Database. The operations team needs to join the streaming sensor data with the historical maintenance records in near real-time to detect anomalies, and data scientists need to run ad-hoc T-SQL queries on the combined dataset for analysis. Which Azure service should they use as the primary analytics platform to meet both requirements?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "primary"
Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
Why wrong: Azure Stream Analytics handles real-time stream processing but cannot perform ad-hoc T-SQL queries on historical data.
B
Azure Databricks
Why wrong: Azure Databricks can process streaming and batch data, but it uses Spark SQL, not T-SQL, and the question specifies T-SQL as a requirement.
C
Azure Synapse Analytics
Azure Synapse Analytics provides both real-time ingestion and a T-SQL-based query engine (SQL pool or serverless) for ad-hoc analysis, meeting both requirements.
D
Azure Analysis Services
Why wrong: Azure Analysis Services creates semantic models for reporting, but does not directly process streaming data or support ad-hoc T-SQL queries on raw data.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Synapse Analytics
Azure Synapse Analytics is the correct choice because it provides a unified analytics platform that can ingest streaming data from Azure Event Hubs via its built-in Spark pools or pipelines, and simultaneously query historical data in Azure SQL Database using T-SQL. This enables near real-time anomaly detection through streaming joins and ad-hoc T-SQL queries for data scientists, all within a single service without needing separate tools.
Key principle: Azure Synapse Analytics unifies data warehousing, big data analytics, and data integration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics handles real-time stream processing but cannot perform ad-hoc T-SQL queries on historical data.
✗
Azure Databricks
Why it's wrong here
Azure Databricks can process streaming and batch data, but it uses Spark SQL, not T-SQL, and the question specifies T-SQL as a requirement.
✓
Azure Synapse Analytics
Why this is correct
Azure Synapse Analytics provides both real-time ingestion and a T-SQL-based query engine (SQL pool or serverless) for ad-hoc analysis, meeting both requirements.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Azure Synapse Analytics unifies data warehousing, big data analytics, and data integration.
✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services creates semantic models for reporting, but does not directly process streaming data or support ad-hoc T-SQL queries on raw data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Stream Analytics as sufficient for both requirements, overlooking its lack of ad-hoc T-SQL query support, and mistakenly think Azure Databricks supports T-SQL natively when it actually uses Spark SQL or Python.
Detailed technical explanation
How to think about this question
Azure Synapse Analytics unifies big data and data warehousing by providing both serverless and dedicated SQL pools, along with Apache Spark pools for streaming ingestion from Event Hubs. The near real-time join can be achieved using Synapse Pipelines or Spark Structured Streaming, while the dedicated SQL pool supports T-SQL queries with high concurrency and columnstore indexes for fast analytics. A subtle behavior is that Synapse’s serverless SQL pool can query data directly from Azure Data Lake Storage without loading it, enabling cost-effective ad-hoc analysis on combined datasets.
KKey Concepts to Remember
Azure Synapse Analytics unifies data warehousing, big data analytics, and data integration.
It offers both serverless and dedicated SQL pools for T-SQL querying.
Synapse can ingest and process streaming data from sources like Azure Event Hubs.
It supports joining real-time data with historical data for comprehensive analysis.
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
Azure Synapse Analytics unifies data warehousing, big data analytics, and data integration.
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. Azure Synapse Analytics unifies data warehousing, big data analytics, and data integration. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
Review azure Synapse Analytics unifies data warehousing, big data analytics, and data integration., then practise related DP-900 questions on the same topic to reinforce the concept.
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Azure Synapse Analytics unifies data warehousing, big data analytics, and data integration..
What is the correct answer to this question?
The correct answer is: Azure Synapse Analytics — Azure Synapse Analytics is the correct choice because it provides a unified analytics platform that can ingest streaming data from Azure Event Hubs via its built-in Spark pools or pipelines, and simultaneously query historical data in Azure SQL Database using T-SQL. This enables near real-time anomaly detection through streaming joins and ad-hoc T-SQL queries for data scientists, all within a single service without needing separate tools.
What should I do if I get this DP-900 question wrong?
Review azure Synapse Analytics unifies data warehousing, big data analytics, and data integration., then practise related DP-900 questions on the same topic to reinforce the concept.
Are there clue words in this question I should notice?
Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
What is the key concept behind this question?
Azure Synapse Analytics unifies data warehousing, big data analytics, and data integration.
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