Machine learning for Mainframe isn’t the future — it’s the present.
While the concepts which animate machine learning may seem complex, the analytical benefits of the technology are clear as day. Backed by a technology that recognizes patterns at an unprecedented efficiency, machine learning tracks data points and develops relationships to help deliver new, actionable analytical insights to IT teams of any size.
Logistically speaking, machine learning observes data and makes decisions or predictions without explicitly being programmed to do so. Essentially, machine learning teaches itself by analyzing data and uses this knowledge to perform tasks, offer insights, and optimize functionality. In the world of IT, machine learning offers a realistic and affordable way to improve the efficiency and cost of mainframe analytics.
Closing the IT knowledge gap
Before you write off machine learning as just another expensive toy employed by major players to keep the little guy down, consider how the technology can be scaled for the purposes of your IT team. Machine learning doesn’t have to upend every process. Employ it sparingly with the most data-intensive, laborious processes to maximize ROI and find quick wins.
Take IT Operations Analytics (ITOA) as a representative example. As IT professionals know, ITOA is the process of obtaining and analyzing data for IT operations. This means recognizing patterns with the goal of discovering new optimization opportunities and, more importantly, detecting anomalies that could affect mainframe performance.
But, this crucial process hinges on the valuable expertise of select individuals.
Every IT team has them: the mainframe oracles who know the environment inside and out. These people have become essential to the ITOA process and, since they are so familiar with the operating environment, they can handpick actionable insights from a messy collection of uncontextualized data. But, there will come a day when these people retire, and with their departure goes your mainframe analytics. It’s not sustainable, and IT teams should consider adopting machine learning as the new resident mainframe expert.
Optimize ITOA with machine learning
Machine learning can learn your mainframe environment faster than any one human ever could. By running behind the scenes, machine learning refines its insights with every data point and contextualizes raw figures into actionable improvements.
The greatest value of machine learning for ITOA is its scalable way to understand what behavior is typical for the environment. No longer will the analytical burden fall solely on the shoulders of the most experienced IT professionals — machine learning algorithms are able to study mainframe data independently and without any human interaction. As it learns the environment, it passes this insight on to the team. Machine learning understands what is standard for a given mainframe environment and can send out alerts anytime an anomaly is detected.
The efficiency of machine learning for detecting system anomalies is unrivaled. Say goodbye to manually inputting KPIs to instruct the mainframe when to send out alerts. Unlike thresholds, machine learning doesn’t have to be controlled manually, because it teaches itself to work independently and automatically — accounting for variability in a way no IT professional can match. Machine learning addresses the shortcomings of thresholds by instituting autonomous data insights.
Machine learning can be your next mainframe expert. For IT teams which struggle to provide consistent service quality, suffer from an unsustainable budget, or lack overall insight into how their mainframe system operates, machine learning is the answer.
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