Match each data transformation concept to its definition.
Drag a concept onto its matching description — or click a concept then click the description.
Handling flexible columns that change over time
Timestamp to track incremental data processing
Optimization to read only relevant partitions
Merge insert and update operations into a single action
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
PolyBase: A technology that allows querying external data sources like Hadoop or Azure Blob Storage using T-SQL.
The correct matches are: PolyBase queries external data via T-SQL; Data Lake is a raw data repository; ELT loads before transforming; Azure Data Factory is a cloud integration service. Common confusions include mixing up PolyBase with Data Lake, or ELT with Azure Data Factory.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
PolyBase: A technology that allows querying external data sources like Hadoop or Azure Blob Storage using T-SQL.
Why this is correct
PolyBase is correctly defined as a technology to query external data with T-SQL.
Data Lake: A centralized repository that stores all data, both structured and unstructured, at any scale.
Why this is correct
Data Lake is correctly defined as a centralized raw data repository.
ELT: A data integration process where data is extracted, loaded into the target system, and then transformed.
Why this is correct
ELT is correctly defined as extract-load-transform process.
Azure Data Factory: A fully managed, serverless data integration service for ingesting, preparing, and transforming data at scale.
Why this is correct
Azure Data Factory is correctly defined as a cloud data integration service.
PolyBase: A storage repository that holds a vast amount of raw data in its native format.
Why it's wrong here
Incorrect — this definition describes Data Lake, not PolyBase.
ELT: A cloud-based data integration service that orchestrates and automates data movement and transformation.
Why it's wrong here
Incorrect — this definition describes Azure Data Factory, not ELT.
Go deeper
Learn chapter
Introduction to Azure Data Engineering
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
Key term
Data Transformation Pipelines
Data transformation pipelines are automated sequences of steps that take raw data from a source, clean and reshape it into a usable format, and then load it into a destination for analysis or storage.
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This DP-203 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-203 exam.