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What is batch processing in data analytics? - Answer-
Batch processing is a method where multiple data records
are collected and stored, then processed together in a
single operation at scheduled intervals or when a certain
amount of data is available.
What is a common real-world example of batch
processing? - Answer-A common example is credit card
billing, where customers receive a single monthly bill
summarizing all their purchases rather than a bill for each
transaction.
What is one advantage and one disadvantage of batch
processing? - Answer-Advantage: It can process large
volumes of data efficiently, often scheduled during off-peak
hours.
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Disadvantage: It introduces a time delay, as data is
processed only after the entire batch is ready.
What is stream processing, and when is it useful? -
Answer-Stream processing continuously processes data in
real time as new events occur. It's useful for time-sensitive
applications that require immediate responses, such as
stock market monitoring or IoT device data.
Provide a real-world example of stream processing. -
Answer-An example is real-time tracking of stock prices,
where data is processed instantly to adjust investment
portfolios in response to market changes.
What is one advantage and one disadvantage of stream
processing? - Answer-Advantage: It enables real-time,
low-latency processing, suitable for instant decision-
making.
Disadvantage: Stream processing typically only handles
recent data within a limited time window and can be more
complex to implement.