2018 will see much broader acceptance of ML and highly predictive analytics into core business decision making at the enterprise level
The major transformation forces of the digital business –DevOps, digitalization, IoT, escalating security threats, and the explosion in complexity of hybrid infrastructure – bring with them a need to change how we manage the technology of business. At every step, as businesses adopt new platforms, move faster, shorten development and delivery cycles, and embrace the opportunities of IoT, the complexity of managing all that technology grows. Simply ask any security operations team about the complexity of threats and the nature of the landscape they deal with day-in and day-out, and it’s clear that the nature of digitalization is one rooted in more information moving more quickly than ever before.
As businesses adopt new platforms, and adapt existing systems to work alongside emerging technologies, how can IT operations and security teams balance the pressures of enabling the use of all that information without having to deal with an unacceptable level of risk? They need help, and the power of analytic tools, rich data gathering and processing, and machine learning, are likely to be where they look first.
Next year will see two trends become more mainstream in the way CIOs plan to deliver the digital transformation their business demands. The first is the adoption of explicit analytic technologies designed to ingest large volumes of operation, configuration, and security data, and deliver insight and intelligence to the operations teams tasked with keeping the lights without compromising security. Coupled with big data, these analytic tools will likely embed machine learning capabilities to not only facilitate better use of data to answer the questions the teams need, but also to help them frame the questions they should be asking. As 2018 progresses, we should expect to see more and more business and operational decisions made on the basis of the questions they told us to ask, not just of the answers analytic tools give.
Secondly, we should expect to see micro-analytic capabilities. That is, technologies to provide use-case specific analytic capabilities designed to augment the broad analytic tools described above, but tuned and tailored for specific uses within the technology teams, security teams, and of course business teams. The embedding of analytics in other tools will provide a broad base of intelligence to build on, and should be used to help overworked operations and security teams deal with the massive complexity of all those moving parts in the hybrid infrastructure of the next decade.
2018 will undoubtedly continue to bring more and more complexity to those tasked with managing the digital business, and the security and privacy of data. But, it also offers the promise of an new set of machine-based allies, with the analytic capabilities to solve the complex problems we probably haven’t even thought of yet.