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DP-700 · Question #52

DP-700 Question #52: Real Exam Question with Answer & Explanation

The correct answer is B: Create a single pipeline with multiple activities for each data source.. When ingesting data from multiple distinct sources into a data pipeline, the most effective design strategy is to centralize the process within a single pipeline containing separate activities for each source.

Design and implement data ingestion and transformation

Question

You need to create a pipeline to ingest data from a variety of sources, including SQL Server databases, CSV files, and JSON files. Which of the following pipeline design strategies would be most effective?

Options

  • ACreate a separate pipeline for each data source.
  • BCreate a single pipeline with multiple activities for each data source.
  • CCreate a pipeline with a lookup activity to determine the data source.
  • DCreate a pipeline with a script activity to dynamically create activities for each data source.

Explanation

When ingesting data from multiple distinct sources into a data pipeline, the most effective design strategy is to centralize the process within a single pipeline containing separate activities for each source.

Common mistakes.

  • A. Creating a separate pipeline for each data source leads to increased management overhead and complexity, especially as the number of sources grows, making it less effective.
  • C. A lookup activity is typically used to retrieve configuration data or parameterize subsequent activities, not to determine the entire data source type and dynamically switch ingestion logic.
  • D. Using a script activity to dynamically create other activities introduces significant complexity and maintenance overhead; standard activities within a single pipeline are generally sufficient and more robust for varied ingestion tasks.

Concept tested. Data ingestion pipeline design for multiple sources

Reference. https://learn.microsoft.com/en-us/fabric/data-factory/copy-data-overview

Topics

#Data Ingestion#Pipeline Design#Azure Data Factory#Data Integration

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