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Linked Services and Datasets in Azure Data Factory

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10 questions
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  • Q1
    What is the primary function of a Linked Service in Azure Data Factory?
    Define the structure of data within a data store.
    Transform data during a data pipeline execution.
    Establish a connection to an external data source.
    Schedule and trigger data factory pipelines.
  • Q2
    Linked Services can be compared to what concept?
    Connection strings
    Data transformations
    Data pipelines
    Data schemas
  • Q3
    A Dataset in Azure Data Factory acts as a reference to what?
    The entire data factory instance.
    A specific data processing activity within a pipeline.
    A specific data object within a linked data store.
    The security settings applied to data access.
  • Q4
    When creating a Dataset, which comes first?
    Defining the data transformation logic.
    Specifying the desired output format.
    Creating a Linked Service to the data source.
    Scheduling the data pipeline execution.
  • Q5
    Datasets can be used for which of the following purposes in Azure Data Factory?
    Neither as a source nor a destination, but for data transformation.
    Both as a source and a destination for data.
    Only as the source of data for a pipeline.
    Only as the destination for data processing results.
  • Q6
    Linked Services support connections to a wide range of data sources. Which of these is NOT a commonly used connection type?
    Social media platform APIs (e.g., Twitter, Facebook)
    Azure Blob Storage
    Oracle database
    SQL Server database
  • Q7
    How can you improve the reusability of Linked Services in Azure Data Factory?
    By using the same Linked Service name for all data sources.
    By embedding connection details directly within data pipelines.
    There is no concept of reusability for Linked Services.
    By creating named Linked Services with specific connection configurations.
  • Q8
    What benefits do Datasets provide in data pipelines?
    They automatically perform data encryption during processing.
    They enable real-time data processing capabilities.
    They simplify data source references and improve code maintainability.
    They allow for complex data validation logic.
  • Q9
    When troubleshooting data pipeline issues in Azure Data Factory, which of these elements should be examined first?
    The output format settings for the final dataset.
    Data transformation activities within the pipeline.
    The scheduling trigger for the data pipeline.
    The configuration of the Linked Services used.
  • Q10
    Azure Data Factory offers several connectors for interacting with cloud services. Datasets, however, define the data structure for what type of data?
    Cloud service configurations.
    The visual layout of data pipelines.
    Code libraries used for data transformations.
    Structured data within data stores.

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