AI can help with DCIM, but only if the data is good enough, says Rene Pronovost

Data center infrastructure management (DCIM) software should be able to use artificial intelligence techniques to understand and forecast problems and requirements - but it can only do this with good enough data, says Rene Pronovost, director of operations for Datacenter Clarity LC at Canadian software firm Maya Heat Transfer Technologies (Maya HTT).

AI-readiness, integration, usability and accessibility are all features Maya added or improved in the latest version of Clarity LC, the data center infrastructure management (DCIM) platform the company has been developing for the last ten years. Pronovost discussed these features at the DCD>Canada 4.0 in Toronto in December 2017.

Good data with a bad AI - better than the reverse

”We’ve been doing AI projects for years,and from our experience it all comes down to the data,” he said. ”In AI projects the challenge comes down to getting good quality data. You often hear that good data with a bad AI is better than bad data with a good AI. It all comes down to having the right data. That all comes down to its labeling, its organization and its classification.”

In many parts of the world, Datacenter Clarity LC is best known as a product sold by Siemens.