DP-200 Azure Data Integration and Migration 2 — Questions and Answers
Question 1: What is the role of Integration Runtime (IR) in Azure Data Factory?
- To store pipeline definitions and metadata
- To provide the compute infrastructure that executes data integration activities (Correct answer)
- To schedule pipeline triggers at defined intervals
- To generate reports on data lineage
Correct answer: To provide the compute infrastructure that executes data integration activities
Integration Runtime is the compute infrastructure Azure Data Factory uses to run activities, providing data movement, data transformation, and SSIS package execution capabilities.
Question 2: Which type of Azure Data Factory Integration Runtime must be installed on an on-premises machine to access private network data sources?
- Azure Integration Runtime
- Azure-SSIS Integration Runtime
- Self-hosted Integration Runtime (Correct answer)
- Hybrid Integration Runtime
Correct answer: Self-hosted Integration Runtime
Self-hosted Integration Runtime is installed on on-premises or cloud VMs in a private network, allowing Azure Data Factory to reach data sources not exposed to the public internet.
Question 3: What do Linked Services represent in Azure Data Factory?
- Logical groupings of pipeline activities
- Connection strings and authentication details for external data stores (Correct answer)
- References to datasets used across multiple pipelines
- Scheduled trigger definitions
Correct answer: Connection strings and authentication details for external data stores
Linked Services in Azure Data Factory function like connection strings, storing the endpoint and credentials required to connect ADF to external data sources and compute resources.
Question 4: Which Azure Data Factory trigger type fires pipelines on a recurring wall-clock schedule, such as every day at 8:00 AM UTC?
- Tumbling window trigger
- Schedule trigger (Correct answer)
- Storage event trigger
- Custom event trigger
Correct answer: Schedule trigger
Schedule triggers fire pipelines based on wall-clock time on a recurring basis (e.g., daily, weekly), making them suitable for time-based batch workloads.
Question 5: Which Azure Data Factory feature provides a visually designed, code-free interface for building complex data transformation logic that runs on Spark?
- Data Flow
- Pipeline Editor
- Mapping Data Flow (Correct answer)
- Copy Data wizard
Correct answer: Mapping Data Flow
Mapping Data Flow lets you visually design data transformations using a graph-based UI; ADF compiles these flows into Spark jobs that run on an auto-managed Spark cluster.
Question 6: Which Azure Data Factory capability allows a single dataset definition to serve multiple data sources by accepting runtime-provided values?
- Schema mapping
- Parameterization (Correct answer)
- Linked service chaining
- Dataset cloning
Correct answer: Parameterization
Parameterization lets you define datasets and linked services with parameters so that a single definition can dynamically point to different tables, files, or databases at runtime.
Question 7: In Azure Data Factory, which construct is a logical grouping of activities that together perform a unit of work?
- Dataset
- Linked Service
- Pipeline (Correct answer)
- Trigger
Correct answer: Pipeline
A Pipeline in Azure Data Factory is a logical grouping of activities—such as Copy, Data Flow, and stored procedure activities—that together accomplish a data integration task.
DP-200 Azure Data Integration and Migration 2
What is the role of Integration Runtime (IR) in Azure Data Factory?