In organisations, it’s clear that data is important for marketing purposes and other fields like identity and access management (IAM). However, there is a distinction between data being important and being valuable. Data has the potential to be valuable, but the actual value largely depends on the processing that was – or was not – applied to the data.
The processing power of machine learning is particularly suitable to spot patterns and anomalies in data streams, and thus reveal security breaches and non-compliance issues. True, the same can be achieved using traditional tools, but not as quickly, nor thoroughly as when using AI.