From the course: Data Planning, Strategy, and Compliance for AI Initiatives

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Real-time data integration patterns

Real-time data integration patterns

From the course: Data Planning, Strategy, and Compliance for AI Initiatives

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Real-time data integration patterns

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- [Instructor] One of the design issues we need to think about when we're talking about any kind of real-time data or event-driven architecture is the ability to integrate data in real time. Now, real-time data integration enables the continuous synchronization of data across multiple systems, and we can do this with minimal latency. Now, this capacity allows AI models to operate on current rather than historical states, so this ability to provide up-to-the-moment insights is really important in a lot of business applications, so for example, it's really critical for time-sensitive decision making. Again, fraud is a perfect example where we need to make decisions very quickly. Now, real-time data integration can also help bridge the traditional gap that we see between operational and analytic data environments, allowing them to work together more effectively. And in many ways, real-time data integration forms, it's almost like the central control system for modern AI-powered…

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