AZ-900 Describe Azure architecture and services Practice Question

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 Synapse Analytics

  Why it's wrong here

  Azure Synapse Analytics is an integrated analytics service that unifies data warehousing, big data analytics, and data integration into a single cloud platform. While it includes pipeline capabilities inherited from Azure Data Factory, its primary purpose is enabling query and analysis of data at scale, not serving as a standalone managed ETL service for creating data movement pipelines. The question specifically asks for a service whose focus is on moving and transforming data, which is the core identity of Azure Data Factory, not Synapse.

• ✓

  Azure Data Factory

  Why this is correct

  Azure Data Factory is the correct answer because it is the managed cloud-based ETL service explicitly designed for creating data-driven pipelines that move and transform data. It enables you to define linked services, datasets, and activities to copy data from source to destination, and you can use control flow and data flows for transformation. This capability aligns directly with the question's description, making it the only option that fits.

• ✗

  Azure Databricks

  Why it's wrong here

  Azure Databricks is an Apache Spark-based analytics platform designed for big data engineering and machine learning, not for orchestrating data movement pipelines. It provides interactive workspaces and clusters for processing and analyzing large datasets, whereas Azure Data Factory is the managed ETL service specifically built for creating, scheduling, and monitoring data integration pipelines. Therefore, its role does not match the description of a service for creating data-driven pipelines that move and transform data.

• ✗

  Azure Stream Analytics

  Why it's wrong here

  Azure Stream Analytics is a real-time event-processing engine that runs continuous, declarative queries on streaming data from sources like IoT Hub or Event Hubs. It does not orchestrate batch ETL pipelines or manage scheduled data movement; instead, it reacts to data as it arrives. The question describes a service for creating data-driven pipelines to move and transform data, which is a batch-oriented ETL task that Stream Analytics does not perform.