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Answer: Micro-batching
Batch processing (A) is suitable for processing large volumes of data, but it may not be efficient for handling varying data formats. Stream processing (B) and real-time processing (D) are designed for processing data in real-time, but they may not be the best choice for handling large volumes of data with varying formats. Micro-batching (C) is a technique that combines the benefits of both batch and stream processing, allowing for efficient processing of large volumes of data with varying formats by breaking the data into smaller, manageable batches.
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In a data engineering project, you are tasked with designing a data pipeline that needs to handle a large volume of data with varying data formats. Which of the following data processing techniques would be most suitable for this task, and why?
A
Batch processing
B
Stream processing
C
Micro-batching
D
Real-time processing
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