What are the reasons for using parallel transformation?

Parallel transformation is used to enhance performance and efficiency in data processing by allowing multiple processes to execute simultaneously. This approach reduces processing time, particularly for large datasets, by leveraging the capabilities of multi-core processors or distributed computing environments. Additionally, it improves resource utilization and can lead to faster response times in applications requiring real-time data processing. Lastly, parallel transformation can simplify complex tasks by breaking them into smaller, manageable parts that can be executed concurrently.