Applying subject matter expertise to process data streams for accuracy is a necessary part of mining’s new digital age, according to SRK Consulting Global chief technology officer Mike Olsen.
Olsen, the leader of SRK’s data engineering team, spoke to Mining Weekly in a Zoom interview from Canada.
Basing analysis solely on data, without first applying subject matter know-how to verify it, runs the risk of valuable information - 'treasure' - being mistaken for trash. In the rough world of mining, those who focus exclusively on the data can easily mislabel as ‘garbage’ what technical discipline experts can identify as valuable data.
A mine site is not a pristine datacentre; field stations get bumped, dataloggers are moved, cables are cut, drop-in sensors get snagged, and people fail to do things in the exact way that today’s digital native practitioners assume happen consistently every time. Applying subject matter expertise to data must occur prior to analysis because no sensor will always be 100% reliable, nor will the right information invariably be delivered on the right schedule.
“A huge stream of unverified data coming at you in enormous volume and incredible velocity isn’t of much value. Regardless of scale, you want verified data for analysis,” Olsen emphasises, pointing to the telling graphic of the two suited data experts, above, declaring as ‘garbage’ what a delighted on-site operative identifies as 'gold'.
“Without a solid understanding of the site, its operations, the actual mechanics of data collection, and a technical understanding of the data itself, too much of a mine site’s data will appear as noise to the uninitiated data expert. “Garbage in, garbage out” is a paradigm for the datacentre. Data from a mine is signal rich but only for those with the background to tune the dials,” says Olsen.
Read the full article on Mining Weekly
