This DP-900 practice question tests your understanding of describe core data concepts. 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 designing a data pipeline for a social media analytics platform. The pipeline needs to ingest posts from multiple sources (Twitter, Facebook) in real time, transform the data by adding sentiment scores, and store the results in a data store for later analysis. The transformation logic is simple and can be expressed as a SQL query. You want to minimize coding effort. Which Azure service should you use for the transformation step?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
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.
Azure Data Factory
Why wrong: Primarily batch ETL, not real-time streaming.
Azure Databricks
Why wrong: Overkill for simple SQL transformations; requires Spark code.
Azure Functions
Why wrong: Requires writing code; not SQL-based.
Azure Stream Analytics
SQL-based transformation for streaming data, low-code.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Azure Stream Analytics
Azure Stream Analytics is the correct choice because it is designed for real-time data processing with SQL-like query language, allowing you to transform streaming data (e.g., from Twitter and Facebook) by adding sentiment scores using simple SQL expressions without writing custom code. It integrates natively with Azure Event Hubs or IoT Hub for ingestion and outputs to Azure SQL Database, Cosmos DB, or Blob Storage for analysis, minimizing coding effort.
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.
Azure Data Factory
Why it's wrong here
Primarily batch ETL, not real-time streaming.
Azure Databricks
Why it's wrong here
Overkill for simple SQL transformations; requires Spark code.
Azure Functions
Why it's wrong here
Requires writing code; not SQL-based.
Azure Stream Analytics
Why this is correct
SQL-based transformation for streaming data, low-code.
Clue confirmation
The clue word "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 confuse Azure Data Factory (batch ETL) with real-time stream processing, or assume Azure Functions is simpler for SQL-like transformations, but Stream Analytics is the only service that combines real-time ingestion, SQL-based transformation, and minimal coding effort.
Detailed technical explanation
Azure Stream Analytics uses a temporal SQL dialect that supports windowing functions (e.g., TumblingWindow, HoppingWindow) and built-in machine learning functions like AnomalyDetection for sentiment scoring, all executed in-memory with sub-second latency. Under the hood, it leverages a distributed stream processing engine that partitions data across nodes for scalability, and it can handle up to 1 GB/s throughput per job. A real-world scenario is a social media dashboard that needs to compute average sentiment per minute across millions of posts, where Stream Analytics can output directly to Power BI for live visualization.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Describe core data concepts — study guide chapter
Learn the concepts, then practise the questions
Describe core data concepts practice questions
Targeted practice on this topic area only
All DP-900 questions
982 questions across all exam domains
Microsoft Azure Data Fundamentals DP-900 study guide
Full concept coverage aligned to exam objectives
DP-900 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise DP-900 questions linked to Describe core data concepts.
Practise DP-900 questions linked to Describe an analytics workload on Azure.
Practise DP-900 questions linked to Identify considerations for relational data on Azure.
Practise DP-900 questions linked to Describe considerations for working with non-relational data on Azure.
Practise DP-900 questions linked to DP-900 fundamentals.
Practise DP-900 questions linked to DP-900 scenario.
Practise DP-900 questions linked to DP-900 troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Describe core data concepts — This question tests Describe core data concepts — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Stream Analytics — Azure Stream Analytics is the correct choice because it is designed for real-time data processing with SQL-like query language, allowing you to transform streaming data (e.g., from Twitter and Facebook) by adding sentiment scores using simple SQL expressions without writing custom code. It integrates natively with Azure Event Hubs or IoT Hub for ingestion and outputs to Azure SQL Database, Cosmos DB, or Blob Storage for analysis, minimizing coding effort.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 24, 2026
This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.