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Develop data processing →hardMultiple ChoiceObjective-mapped

Replace NULLs with Mapping Data Flow — Derived Column Transformation | Azure Data Engineer Associate Explained

This DP-203 practice question tests your understanding of develop data processing. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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

{
  "name": "CopyDataFromBlobToSynapse",
  "properties": {
    "activities": [
      {
        "name": "CopyData",
        "type": "Copy",
        "inputs": [{"referenceName": "BlobSource", "type": "DatasetReference"}],
        "outputs": [{"referenceName": "SynapseSink", "type": "DatasetReference"}],
        "typeProperties": {
          "source": {
            "type": "DelimitedTextSource",
            "storeSettings": {
              "type": "AzureBlobStorageReadSettings",
              "recursive": true
            }
          },
          "sink": {
            "type": "SqlPoolSink",
            "writeBatchSize": 10000,
            "preCopyScript": "TRUNCATE TABLE dbo.Sales"
          },
          "translator": {
            "type": "TabularTranslator",
            "mappings": [
              {"source": "ProductID", "sink": "ProductID"},
              {"source": "SaleDate", "sink": "SaleDate"},
              {"source": "Quantity", "sink": "Quantity"},
              {"source": "Amount", "sink": "Amount"}
            ]
          }
        }
      }
    ]
  }
}

Refer to the exhibit. You have an Azure Data Factory pipeline that copies data from a CSV file in Blob Storage to a Synapse dedicated SQL pool table named dbo.Sales. The pipeline fails. The error message indicates that the 'Amount' column in the sink table does not allow NULLs but the source contains NULL values. What is the best way to resolve this issue without losing data?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "best"

    Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

Exhibit

{
  "name": "CopyDataFromBlobToSynapse",
  "properties": {
    "activities": [
      {
        "name": "CopyData",
        "type": "Copy",
        "inputs": [{"referenceName": "BlobSource", "type": "DatasetReference"}],
        "outputs": [{"referenceName": "SynapseSink", "type": "DatasetReference"}],
        "typeProperties": {
          "source": {
            "type": "DelimitedTextSource",
            "storeSettings": {
              "type": "AzureBlobStorageReadSettings",
              "recursive": true
            }
          },
          "sink": {
            "type": "SqlPoolSink",
            "writeBatchSize": 10000,
            "preCopyScript": "TRUNCATE TABLE dbo.Sales"
          },
          "translator": {
            "type": "TabularTranslator",
            "mappings": [
              {"source": "ProductID", "sink": "ProductID"},
              {"source": "SaleDate", "sink": "SaleDate"},
              {"source": "Quantity", "sink": "Quantity"},
              {"source": "Amount", "sink": "Amount"}
            ]
          }
        }
      }
    ]
  }
}

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

✓

Use a Mapping Data Flow with a Derived Column transformation to replace NULLs with 0

Option A is correct because a Mapping Data Flow with a Derived Column transformation allows you to replace NULL values in the 'Amount' column with a default value (e.g., 0) before writing to the Synapse dedicated SQL pool. This resolves the NULL constraint violation without losing any rows, as the data is transformed inline within the pipeline. The copy activity alone cannot perform such transformations, making the Mapping Data Flow the appropriate choice for this ETL scenario.

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.

  • ✓

    Use a Mapping Data Flow with a Derived Column transformation to replace NULLs with 0

    Why this is correct

    Mapping Data Flow allows you to handle NULLs by providing a default value, ensuring data integrity.

    Clue confirmation

    The clue word "best" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • ✗

    Add a filter in the copy activity to exclude rows with NULL Amount

    Why it's wrong here

    Filtering would lose data, which is not ideal.

  • ✗

    Modify the sink table to have a default value for the Amount column

    Why it's wrong here

    Setting a default value does not help if the source provides NULLs; the copy activity would still fail.

  • ✗

    Change the sink table column to allow NULLs

    Why it's wrong here

    This may not be permitted due to business requirements and could cause issues later.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often assume a default value on the column will automatically replace NULLs during a bulk insert, but in Azure Synapse and most SQL databases, a default only applies when the column is not referenced in the INSERT statement, not when NULL is explicitly provided.

Detailed technical explanation

How to think about this question

Under the hood, the Synapse dedicated SQL pool enforces NOT NULL constraints at the table level, and the copy activity's default behavior is to map source columns directly to sink columns without transformation. A Mapping Data Flow runs on Spark clusters and can apply row-by-row transformations like coalesce() in a Derived Column to replace NULLs, which is more flexible than using a staging table or external script. In real-world scenarios, this approach is critical when source data has sporadic NULLs but the target schema must remain unchanged for reporting integrity.

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.

Visual reference

Client Recursive Resolver Root DNS (13 root servers) TLD DNS (.com, .org, …) Authoritative example.com query IP addr answer

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-203 question test?

Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Use a Mapping Data Flow with a Derived Column transformation to replace NULLs with 0 — Option A is correct because a Mapping Data Flow with a Derived Column transformation allows you to replace NULL values in the 'Amount' column with a default value (e.g., 0) before writing to the Synapse dedicated SQL pool. This resolves the NULL constraint violation without losing any rows, as the data is transformed inline within the pipeline. The copy activity alone cannot perform such transformations, making the Mapping Data Flow the appropriate choice for this ETL scenario.

What should I do if I get this DP-203 question wrong?

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

Are there clue words in this question I should notice?

Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jul 4, 2026

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