As a CIO, if your enterprise relies on solutions that look like something out of the 1990s, it's often because that's exactly what they are. These applications - ERPs and home-grown core operations systems met an immediate business need at the time, then layer upon layer was built on top and entrenched into the foundational processes of the business. Now you are at a catch-22: pressure to modernize to meet the growing digital needs of the enterprise, while at the same time not risking the legacy software that is vital to day-to-day operations.
How do you prioritize legacy transformation as part of a digital transformation roadmap?
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There’s a lot of excitement in the security world today around artificial intelligence (AI) and, more specifically, machine learning (ML). CSO Online lists their top 5 use cases for machine learning in security which include detecting malicious activity in the network, automating repetitive tasks, and analyzing large volumes of data for threat intelligence. But another immediate application of machine learning will be in data protection and the prevention of data leaks.
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