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In the context of streaming data from multiplex bronze tables in a Databricks environment, consider the following scenario: Your organization requires real-time data processing to support immediate decision-making. The data comes from various sources with varying quality levels, and there's a need to ensure high data quality without introducing significant latency. Additionally, the solution must be cost-effective and scalable to handle increasing data volumes. Which of the following approaches BEST meets these requirements? Choose one option.
A
Stream data from multiplex bronze tables in real-time, without any data transformations or cleaning, to minimize latency and costs.
B
Stream data from multiplex bronze tables in batches, applying data transformations and cleaning after each batch to ensure data quality at the expense of latency.
C
Stream data from multiplex bronze tables in real-time, applying data transformations and cleaning on-the-fly to ensure immediate data availability and quality.
D
Stream data from multiplex bronze tables in batches, without any data transformations or cleaning, to balance between latency and costs.