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 retail company runs a nightly job that reads all sales transactions from the previous day from an operational database, aggregates them by product category and store location, and writes the summary results into a data warehouse for reporting. Which type of data processing workload does this nightly job represent?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
B. Batch processing
The nightly job processes data in discrete, scheduled batches—reading all sales transactions from the previous day, aggregating them, and writing results to a data warehouse. This is the classic definition of batch processing, where data is collected over a period and processed together in a single job run. In Azure, this workload maps to services like Azure Data Factory or Azure Synapse Pipelines executing scheduled pipelines.
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.
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A. Real-time processing
Why it's wrong here
Real-time processing handles data immediately as it is generated; this job runs nightly, not continuously.
✓
B. Batch processing
Why this is correct
Batch processing involves processing a defined set of data at scheduled intervals, such as nightly aggregation jobs.
Related concept
Read the scenario before looking for a memorised answer.
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C. Stream processing
Why it's wrong here
Stream processes data in motion, often in near real-time; this job processes a fixed set of historical data.
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D. Transactional processing
Why it's wrong here
Transactional processing handles individual transactions (OLTP) and ensures ACID properties; this is an analytical (OLAP) batch workload.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'scheduled' or 'periodic' processing with stream processing, but the key differentiator is that batch processing works on a bounded dataset (all data from the previous day) while stream processing works on an unbounded, continuous flow of data.
Detailed technical explanation
How to think about this question
Batch processing jobs like this typically use a time-based window (e.g., nightly) to extract, transform, and load (ETL) data. Under the hood, Azure Data Factory can orchestrate the job using a tumbling window trigger, which ensures exactly-once processing by tracking watermarks. A real-world scenario is a retail chain aggregating daily sales by store and product category to populate a star schema in Azure Synapse Dedicated SQL Pool for historical trend analysis.
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
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. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. 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.
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: B. Batch processing — The nightly job processes data in discrete, scheduled batches—reading all sales transactions from the previous day, aggregating them, and writing results to a data warehouse. This is the classic definition of batch processing, where data is collected over a period and processed together in a single job run. In Azure, this workload maps to services like Azure Data Factory or Azure Synapse Pipelines executing scheduled pipelines.
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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Question Discussion
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