DP-203 Develop data processing Practice Question
You need to incrementally load new and updated records from a source SQL Server database to Azure Synapse Dedicated SQL Pool. The source table has a LastModifiedDate column. Which Azure Data Factory feature should you use to implement incremental loading efficiently?
⚠ Common exam trap
It's easy for candidates to confuse a scheduling mechanism (Schedule trigger) with the actual data processing logic required for incremental loads, or they mistakenly think a single activity like Lookup or Alter Row can handle the entire incremental copy workflow without understanding the need for a watermark pattern.
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
✓
Incremental copy (watermark) pattern using a Lookup activity and a Copy activity
The incremental copy (watermark) pattern using a Lookup activity and a Copy activity is the correct approach because it allows you to query the source table for the maximum LastModifiedDate value (the watermark), store it in a control table or variable, and then use a Copy activity with a WHERE clause to load only rows where LastModifiedDate is greater than the last run's watermark. This pattern is purpose-built for efficiently handling new and updated records in Azure Data Factory without reprocessing the entire dataset.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Alter Row transformation
Why it's wrong here
Alter Row marks rows for insert, update, delete or upsert inside a mapping data flow, but it does not itself identify which source rows changed since the last run. It suits row-level change routing once a delta has been isolated, not extracting that delta from SQL Server.
- ✓
Incremental copy (watermark) pattern using a Lookup activity and a Copy activity
Why this is correct
The watermark pattern uses a Lookup activity to retrieve the maximum LastModifiedDate already copied, then a Copy activity filters the source on LastModifiedDate greater than that value. This satisfies the incremental requirement, moving only new and updated rows rather than reloading the whole table each run.
- ✗
Schedule trigger
Why it's wrong here
A schedule trigger only determines when a pipeline starts; it carries no knowledge of LastModifiedDate, so every run would reload the full table. Triggers are correct for time-based orchestration, but incremental loading requires a watermark value passed into a filtered source query.
- ✗
Lookup activity alone
Why it's wrong here
A Lookup activity only retrieves a value or dataset for use by later activities; it neither filters source rows by LastModifiedDate nor writes to the sink. It is the right building block for fetching the stored watermark, but the copy itself still needs a parameterised source query and a Copy activity.
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