Microsoft Azure Data Engineer Associate - DP-203
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In a scenario where a data pipeline in Azure Data Factory needs to handle data from various sources with different update frequencies, describe how you would design the pipeline to manage these varying data inputs efficiently, including the use of triggers and scheduling mechanisms.
In a scenario where a data pipeline in Azure Data Factory needs to handle data from various sources with different update frequencies, describe how you would design the pipeline to manage these varying data inputs efficiently, including the use of triggers and scheduling mechanisms.
Simulated
Explanation:
Designing the pipeline with multiple triggers, each aligned with the update frequency of a specific source, ensures efficient handling of varying data inputs. Using control flow activities to manage data integration based on these frequencies optimizes resource usage and processing times, enhancing the overall efficiency of the pipeline.