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Describe core data concepts →easyMultiple ChoiceObjective-mapped

Quick Answer

The answer is Azure Data Factory. This JSON configuration defines a pipeline with a copy activity, which is the fundamental building block of Azure Data Factory (ADF) for orchestrating and automating data movement. The structure includes a 'source' pointing to Azure Blob Storage and a 'sink' pointing to Azure SQL Database, with 'typeProperties' detailing the copy behavior—this exact pattern of pipeline, activities, source, and sink is unique to ADF and not used by other Azure data services like Synapse or Data Lake. On the DP-900 exam, this tests your ability to recognize ADF’s core role in extract, transform, and load (ETL) workflows, often appearing as a JSON snippet where a common trap is confusing it with Azure Data Lake Storage or Azure Synapse Analytics, which lack this specific pipeline-activity hierarchy. To remember, think of ADF as the "orchestrator" that uses JSON to define every step of a data journey: the pipeline is the plan, the copy activity is the mover, and source/sink are the endpoints.

DP-900 Describe core data concepts Practice Question

This DP-900 practice question tests your understanding of describe core data concepts. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

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?

Question 1easymultiple choice
Full 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"
    }
  ]
}

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.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

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

    Analysis Services uses tabular models, not datasource definitions like this.

  • ✓

    Azure Data Factory

    Why this is correct

    Data Factory defines linked services and datasets in JSON.

    Related concept

    Read the scenario before looking for a memorised answer.

  • ✗

    Power BI

    Why it's wrong here

    Power BI uses PBIX files, not JSON for datasources.

  • ✗

    Azure Synapse Analytics

    Why it's wrong here

    Synapse uses SQL scripts and pipelines, not this JSON structure.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates 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.

Detailed technical explanation

How to think about this question

Under the hood, the copy activity in ADF uses the Integration Runtime (IR) to connect to sources and sinks, supporting over 90 built-in connectors. The JSON 'typeProperties' section defines the exact dataset references, compression, column mappings, and fault tolerance settings. In real-world scenarios, ADF pipelines can be triggered by events (e.g., blob creation) or schedules, and the copy activity can automatically handle schema drift and data type conversions.

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.

TExam Day Tips

  • 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.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this DP-900 question test?

Describe core data concepts — This question tests Describe core data concepts — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: 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.

What should I do if I get this DP-900 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 24, 2026

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This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.