Near-real-time delivery of data and insights enable businesses to rapidly respond to their customers’ needs. Real-time data can come from a variety of sources, including social media, IoT devices, infrastructure monitoring, call center monitoring, and more. Due to the breadth and depth of data being ingested from multiple sources, businesses look for solutions to protect their customers’ privacy and keep sensitive data from being accessed from end systems. You previously had to rely on personally identifiable information (PII) rules engines that could flag false positives or miss data, or you had to build and maintain custom machine learning (ML) models to identify PII in your streaming data. You also needed to implement and maintain the infrastructure necessary to support these engines or models.
To help streamline this process and reduce costs, you can use Amazon Comprehend, a natural language processing (NLP) service that uses ML to find insights and relationships

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