- A
Azure Stream Analytics
Why wrong: Azure Stream Analytics provides real-time stream processing but is designed to send output to sinks (e.g., event hubs, storage) rather than support interactive ad-hoc queries on historical data.
- B
Azure Data Explorer
Azure Data Explorer is optimized for high-velocity time-series data, supports near real-time anomaly detection, and enables fast interactive queries on both streaming and historical data using a SQL-like language (KQL).
- C
Azure Synapse Analytics dedicated SQL pool
Why wrong: Azure Synapse dedicated SQL pool is designed for large-scale data warehousing with T-SQL, but it is not optimized for high-frequency time-series ingestion and interactive ad-hoc queries on streaming data.
- D
Azure Databricks with Structured Streaming
Why wrong: Azure Databricks can handle streaming analytics using Spark Structured Streaming, but for interactive ad-hoc queries on live data, it typically has higher latency and requires more complex setup compared to Azure Data Explorer.
Quick Answer
The answer is Azure Data Explorer (ADX). This service is purpose-built for high-velocity IoT telemetry analytics, ingesting terabytes of sensor data per day with sub-second latency and supporting both near-real-time anomaly detection and interactive ad-hoc queries on historical data using Kusto Query Language (KQL), a SQL-like syntax optimized for time-series analysis. On the DP-900 exam, this scenario tests your ability to distinguish Azure Data Explorer from other data services like Azure Stream Analytics or Azure Synapse Analytics; a common trap is choosing Stream Analytics for real-time processing alone, but ADX uniquely combines real-time ingestion with deep historical ad-hoc querying in a single, cost-effective platform. Remember the memory tip: “ADX for AD-hoc eXploration”—if the scenario demands both instant anomaly detection and flexible, SQL-like queries over massive telemetry archives, Azure Data Explorer is the correct choice.
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. 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 manufacturing company connects thousands of IoT sensors on an assembly line, each sending telemetry data every second. The data volume is terabyte-scale per day. The company needs to analyze the sensor data in near real-time to detect anomalies (e.g., temperature spikes) and also allow data scientists to run interactive ad-hoc queries on the historical data to find patterns. They prefer using a query language similar to SQL. Which Azure service should they choose?
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
Azure Data Explorer
Azure Data Explorer (ADX) is designed for high-velocity telemetry data, ingesting terabytes per day from IoT sensors with sub-second latency. It supports Kusto Query Language (KQL), which is SQL-like and optimized for time-series analysis, anomaly detection, and interactive ad-hoc queries on both real-time and historical data. This makes it the ideal choice for the described scenario.
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.
- ✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics provides real-time stream processing but is designed to send output to sinks (e.g., event hubs, storage) rather than support interactive ad-hoc queries on historical data.
- ✓
Azure Data Explorer
Why this is correct
Azure Data Explorer is optimized for high-velocity time-series data, supports near real-time anomaly detection, and enables fast interactive queries on both streaming and historical data using a SQL-like language (KQL).
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Synapse Analytics dedicated SQL pool
Why it's wrong here
Azure Synapse dedicated SQL pool is designed for large-scale data warehousing with T-SQL, but it is not optimized for high-frequency time-series ingestion and interactive ad-hoc queries on streaming data.
- ✗
Azure Databricks with Structured Streaming
Why it's wrong here
Azure Databricks can handle streaming analytics using Spark Structured Streaming, but for interactive ad-hoc queries on live data, it typically has higher latency and requires more complex setup compared to Azure Data Explorer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Azure Stream Analytics because it handles real-time streaming and uses SQL-like syntax, but they overlook the requirement for interactive ad-hoc queries on historical data, which Stream Analytics cannot efficiently support.
Trap categories for this question
Command / output trap
Azure Stream Analytics provides real-time stream processing but is designed to send output to sinks (e.g., event hubs, storage) rather than support interactive ad-hoc queries on historical data.
Detailed technical explanation
How to think about this question
Azure Data Explorer uses a columnar storage engine with a distributed query execution model that leverages a hash-based sharding and a time-partitioned index for fast range scans. Its ingestion pipeline supports batching and streaming, automatically creating inverted indexes for text fields and pre-aggregating data for common queries, which enables sub-second responses even on petabyte-scale datasets. In real-world scenarios, ADX can ingest millions of events per second and answer queries like 'average temperature per sensor over the last 5 minutes' in under 100 milliseconds.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Data Explorer — Azure Data Explorer (ADX) is designed for high-velocity telemetry data, ingesting terabytes per day from IoT sensors with sub-second latency. It supports Kusto Query Language (KQL), which is SQL-like and optimized for time-series analysis, anomaly detection, and interactive ad-hoc queries on both real-time and historical data. This makes it the ideal choice for the described scenario.
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
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.
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