Describe core data concepts →easyMultiple ChoiceObjective-mapped

DP-900 Describe core data concepts Practice Question

Exhibit

{
  "datasources": [
    {
      "name": "SalesDB",
      "connectionString": "Server=tcp:myserver.database.windows.net;Database=Sales;...",
      "type": "AzureSQL"
    },
    {
      "name": "SalesLake",
      "connectionString": "https://mystorage.blob.core.windows.net/sales",
      "type": "AzureBlobStorage"
    }
  ],
  "datasets": [
    {
      "name": "SalesOrders",
      "source": "SalesDB",
      "table": "Orders"
    },
    {
      "name": "SalesFiles",
      "source": "SalesLake",
      "folder": "csv"
    }
  ]
}

Refer to the exhibit. The JSON shows a configuration for which Azure service?

⚠ Common exam trap

It's easy for candidates to confuse the JSON pipeline definition with Azure Synapse Analytics pipelines, which share the same underlying engine but are accessed via a different portal and have additional Synapse-specific features like Spark job definitions and SQL script activities.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Azure Data Factory

The JSON snippet defines a pipeline with a copy activity that moves data from a source (Azure Blob Storage) to a sink (Azure SQL Database). This is the core pattern of Azure Data Factory (ADF), which orchestrates and automates data movement and transformation. The structure with 'name', 'properties', 'activities', 'typeProperties', 'source', and 'sink' is specific to ADF pipeline definitions.

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 Analysis Services
Why it's wrong here
Azure Analysis Services is not the right choice because it consumes tabular or multidimensional models defined in .bim files or .model files via Visual Studio, not JSON datasource definitions like the one shown. While Analysis Services does connect to data sources, it does not use JSON linked services or pipeline artifacts to orchestrate data movement; its metadata for tables, measures, and relationships resides in a model file rather than an integration configuration.
✓
Azure Data Factory
Why this is correct
Azure Data Factory is correct because it represents linked services, datasets, and pipelines as JSON objects. The exhibit shows a linked service definition with a type and typeProperties containing connection details, which is the standard way ADF stores source and destination connection information. This serialized JSON enables version-controlled, repeatable deployment of data integration artifacts.
✗
Power BI
Why it's wrong here
Power BI is wrong because its data connections and queries are stored inside a .pbix binary package, not as standalone JSON configuration files. Power BI uses Power Query M expressions to define data sources, and while it can read JSON as a data format, it does not define linked services or dataset connections with the exact JSON schema shown. The configuration resembles an Azure Data Factory linked service, not a Power BI data source.
✗
Azure Synapse Analytics
Why it's wrong here
Azure Synapse Analytics is not the answer because, although its pipelines inherit Azure Data Factory's JSON-based architecture, the dedicated SQL pool itself relies on T-SQL scripts, external tables, and PolyBase to connect to data sources. The JSON in the exhibit is a linked service definition that belongs to Data Factory's pipeline orchestration model, not to the SQL analytics warehouse interface. If the JSON came from a Synapse pipeline, it would still be a Data Factory artifact, making Azure Data Factory the more direct and correct answer.

Quick reference

Azure Blob Storage Tier Comparison

Tier	Storage Cost	Retrieval Cost	Latency	Use Case
Hot	Highest	Lowest	Immediate	Active data, frequent reads
Cool	Lower	Higher	Immediate	Data accessed < once / month
Cold	Lower still	Higher	Immediate	Data accessed < once / quarter
Archive	Lowest	Highest + rehydration delay	Hours	Long-term compliance retention

Go deeper

DP-900 Describe core data concepts Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

Azure Blob Storage Tier Comparison

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