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Answer: Implement a pipeline that is designed to be flexible and can easily adapt to changes in data requirements or sources, such as using configurable parameters and modular design.
Ensuring that a data pipeline is flexible and can adapt to changing data requirements or sources is important for maintaining its relevance and effectiveness over time. Implementing a pipeline that is designed to be flexible, such as using configurable parameters and modular design, allows it to easily accommodate changes in data requirements or sources. Implementing a rigid pipeline or assuming that the data requirements and sources will not change can result in the pipeline becoming obsolete or unable to meet new requirements. Focusing only on optimizing performance without considering flexibility can limit the pipeline's ability to adapt to changing conditions.
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You are responsible for implementing a data pipeline in Azure Data Factory that integrates data from various sources. How can you ensure that the pipeline is flexible and can adapt to changing data requirements or sources over time?
A
Implement a rigid pipeline that is not designed to accommodate changes in data requirements or sources.
B
Implement a pipeline that is designed to be flexible and can easily adapt to changes in data requirements or sources, such as using configurable parameters and modular design.
C
Focus only on optimizing the performance of the pipeline, ignoring the need for flexibility.
D
Assume that the data requirements and sources will not change over time and do not implement any measures to accommodate changes.
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