The answer is batch processing. This is correct because the hourly copy operation collects data over a fixed one-hour interval and then moves it as a single, discrete unit, which is the defining characteristic of batch processing—handling data in scheduled, non-continuous chunks rather than in real time. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your ability to distinguish between batch and streaming patterns, often using Azure Data Factory pipelines as the key indicator of scheduled, periodic movement. A common trap is confusing scheduled pipelines with streaming, but remember: if there is a fixed time window (like every hour) and data is moved in bulk after collection, it is batch, not streaming. For a quick memory tip, think “Batch = Big, scheduled chunks; Streaming = Steady, continuous flow.”
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 company uses Azure Data Factory to run a pipeline that copies new orders from an on-premises SQL Server database to Azure Data Lake Storage every hour. After the data is in the data lake, an Azure Databricks notebook transforms it and loads it into Azure Synapse Analytics for reporting. Which type of data processing does the hourly copy operation represent?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Batch processing
The hourly copy operation from on-premises SQL Server to Azure Data Lake Storage is a classic batch processing pattern: data is collected over a fixed time interval (1 hour) and processed as a single unit. Azure Data Factory orchestrates this scheduled, non-continuous transfer, which aligns with batch processing's definition of handling data in discrete, periodic chunks rather than in real-time.
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.
✗
Real-time streaming
Why it's wrong here
Real-time streaming processes data continuously as it arrives, not in scheduled hourly batches.
✓
Batch processing
Why this is correct
The hourly copy operation processes data in discrete, scheduled batches, which is the definition of batch processing.
Related concept
Read the scenario before looking for a memorised answer.
✗
Interactive query
Why it's wrong here
Interactive query involves on-demand, user-driven queries against data, not scheduled data movement.
✗
Transactional processing
Why it's wrong here
Transactional processing handles small, frequent read/write operations with ACID properties, not bulk data transfer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse scheduled data movement (batch) with real-time streaming, especially when the pipeline runs frequently (e.g., every hour), but the key distinction is that batch processes data in discrete intervals, not continuously as it arrives.
Detailed technical explanation
How to think about this question
Under the hood, Azure Data Factory's tumbling window trigger schedules the copy activity to execute every hour, using a self-hosted integration runtime to connect to on-premises SQL Server via the Tabular Data Stream (TDS) protocol. The data is staged in Azure Blob Storage or Data Lake Storage as Parquet or CSV files, enabling efficient batch loading into Azure Synapse Analytics via PolyBase or COPY INTO. This pattern is common in ETL workloads where source systems cannot tolerate continuous polling or where downstream transformations require full-hour snapshots.
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 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.
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: Batch processing — The hourly copy operation from on-premises SQL Server to Azure Data Lake Storage is a classic batch processing pattern: data is collected over a fixed time interval (1 hour) and processed as a single unit. Azure Data Factory orchestrates this scheduled, non-continuous transfer, which aligns with batch processing's definition of handling data in discrete, periodic chunks rather than in real-time.
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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