DP-203 Develop data processing Practice Question
You are a data engineer for a global retail company. The company has a hybrid architecture with on-premises SQL Server databases and Azure Synapse Analytics. You need to design a data processing solution that ingests incremental changes from the on-premises SQL Server database (source) into Azure Synapse Analytics (sink) with low latency (under 15 minutes) and high reliability. The source database is 5 TB and experiences high transaction volume during business hours. The solution must minimize impact on the source system and handle schema changes automatically. You have the following options:
Option A: Use Azure Data Factory with a copy activity that uses a watermark column to query incremental changes every 10 minutes. The copy activity writes directly to the Synapse table using PolyBase.
Option B: Use Azure Data Factory with a mapping data flow that reads from the source using a SQL query with a watermark, performs transformations, and writes to Synapse using staging via Blob Storage and PolyBase.
Option C: Use SQL Server Integration Services (SSIS) running on Azure-SSIS Integration Runtime to extract data using change data capture (CDC) and load into Synapse.
Option D: Use Azure Databricks with Auto Loader to ingest files from a staging area that is populated by a separate log-shipping process from the source.
Which option should you choose?
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
✓
Option B
It handles incremental loads with low latency, uses PolyBase for efficient loading, and mapping data flow allows for schema drift handling and transformations without impacting source. Option A lacks schema drift handling. Option C requires SSIS packages and may have higher latency. Option D requires additional log-shipping, increasing complexity and latency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Option C
Why it's wrong here
SSIS is heavier and may not meet 15-min latency.
- ✗
Option A
Why it's wrong here
No schema drift handling; direct PolyBase may fail on schema changes.
- ✗
Option D
Why it's wrong here
Requires additional infrastructure and increases latency.
- ✓
Option B
Why this is correct
Mapping data flow supports schema drift and uses staging for PolyBase.
Go deeper
Related to this question
Learn chapter
Introduction to Azure Data Engineering
Key term
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
Key term
Azure Databricks
Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure that lets data teams prepare data, run machine learning models, and build data pipelines using a single workspace.
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