Question 1harddrag order
Full question →harddrag orderObjective-mapped
A retail company needs to build an analytics pipeline on Azure. They ingest sales data from multiple store systems and an online e-commerce platform. The data must be cleaned, transformed, and loaded into a data warehouse for reporting. The company wants to use a modern ELT (Extract, Load, Transform) approach where raw data is stored first and then transformed. Order the following steps in the correct sequence for this pipeline. (Drag the steps into the correct order.)
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Best answer
Ingest data from sources using Azure Data Factory.
Data ingestion is the first step to bring raw data into Azure.
B
Best answer
Store raw data in Azure Data Lake Storage Gen2.
Raw data is stored in a data lake for persistence and to enable schema-on-read.
C
Best answer
Transform and clean data using Azure Databricks or Synapse Spark.
Transformations are applied after data is stored, which is characteristic of ELT.
D
Best answer
Load transformed data into Azure Synapse Analytics dedicated SQL pool.
The curated data is loaded into a relational data warehouse for efficient querying.
E
Best answer
Build Power BI reports on top of Azure Synapse Analytics.
Reporting is the final step, consuming the data warehouse for dashboards.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Ingest data from sources using Azure Data Factory. — A typical ELT pipeline on Azure follows this sequence: 1) Ingest data from source systems using Azure Data Factory or Event Hubs. 2) Store raw data in a data lake (Azure Data Lake Storage Gen2) for cost-effective storage and schema-on-read flexibility. 3) Use a data processing engine like Azure Databricks or Synapse Spark to clean, transform, and aggregate the data. 4) Load the transformed data into a data warehouse such as Azure Synapse Analytics dedicated SQL pool for fast query performance. 5) Build and publish reports using Power BI connected to the data warehouse. This order ensures data is landed immediately, transformations are applied later (ELT), and reporting is based on curated data.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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