Characteristics of Real-Time Data Processing

BD

Real time processing deals with streams of data that are captured in real-time and processed with minimal latency to generate real-time (or near-real-time) reports or automated responses.

Real-time data processing refers to the processing of data as it is created or generated. This means that the data is processed immediately or with very low latency to provide real-time insights or actions.

The two characteristics of real-time data processing are:

1. Low latency is expected: Latency refers to the time it takes for data to be processed from the point it is created to the point it is available for use. In real-time data processing, low latency is expected, which means that the data should be processed and made available for use as quickly as possible. This is important because real-time data processing is often used for time-sensitive applications, such as fraud detection, sensor data analysis, or stock trading.

2. Data is processed as it is created: Real-time data processing involves processing data as it is created or generated. This means that the data is processed in near-real-time or real-time, allowing for timely insights or actions. For example, if a sensor is monitoring the temperature in a factory, the data is processed as it is created, allowing for real-time alerts if the temperature exceeds a certain threshold.

In contrast, batch processing involves processing large volumes of data at regular intervals (periodically). This means that the data is not processed as it is created, but is instead stored and processed later. Batch processing is often used for applications that don't require real-time insights or actions, such as customer analytics or report generation.

Therefore, the correct answers are B. Low latency is expected and D. Data is processed as it is created.