As data-mining, the Internet of Things and various other utilizations of advancing tech push and blur the boundaries between intended app design and their full functionalities, the battle for consumer attention is driving the development of nexus platforms beyond the business realm and into the hands of regular users.

At this year’s Splunk.CONF event, Chris Kammermann, senior infrastructure engineer at Shazam Entertainment Ltd., joined John Walls (@JohnWalls21) and John Furrier (@furrier), cohosts of theCUBE, from the SiliconANGLE Media team, to talk about the options open to Shazam’s app, the limitations of “app real estate” and how Kammermann sees the possibilities expanding.

Recognizing power

Fitting with the focus of the conference, the initial portion of the discussion concentrated on how Shazam is handling the heavy loads of data coming in from its many users. Kammermann described Shazam’s mixture of data centers, noting that it has “about 30 Splunk indexes,” before moving on to the app and its abilities.

After a real-time demonstration of how the app could use a mobile device’s camera to identify a person and pull up their online bio and LinkedIn page, Kammermann gave some more examples of how the app’s functionality could be applied. Use-cases of recognizing songs as they play, giving information on racecars and their drivers and similar instances were shared, though Kammermann stated, “The Shazam ethos is to be able to do anything.”

Data versatility

Addressing the reliability of the app’s performance in a variety of settings, Kammermann also noted, “Mobile poses its own challenge, Wi-Fi drops in and out … but mobile, it’s a mature environment right now. … It’s really, in some ways, no different to a normal web app.”

More possibilities for Shazam’s app were shared, with a focus on augmented reality enablement through scanning and recognition and a use-case example of a movie poster scan potentially shifting your phone into part of the set.

“We’re trying to sell data to other people as well,” Kammermann shared. “If you want access to our data … you can buy some of that.” Tying into that, he said, Shazam was capable of determining ways to best sell to people through the mining of their gathered data.

As optimistic as Kammermann was, saying, “The sectors we can play in are virtually limitless, it’s just up to us to choose where we want to go. … We can go anywhere with this app, and the future is our oyster,” what really had him excited were the possibilities of machine learning to make further use of its data.

Throwing out one last example of the app’s power, he stated that once that sort of computing is integrated, “I can go play with Shazam data, manipulate it and predict the next #1 song.”

Watch the complete video interview, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of Splunk.conf 2016.

Photo by SiliconANGLE