Artificial Intelligence for Big Data

Real-time processing

While batch processing frameworks are good for most data warehousing use cases, there is a critical need for processing the data and generating actionable insight as soon as the data is available. For example, in a credit card fraud detection system, the alert should be generated as soon as the first instance of logged malicious activity. There is no value if the actionable insight (denying the transaction) is available as a result of the end-of-month batch process. The idea of a real-time processing framework is to reduce latency between event time and processing time. In an ideal system, the expectation would be zero differential between the event time and the processing time. However, the time difference is a function ...