Moving From Data Collection To Decisions and Predictions

Moving From Data Collection To Decisions and Predictions
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At last week’s SplunkLive! event, the company’s global field leader for IT markets, Johnathon Cervelli opened the event, saying the company has continued to grow their business with a focus on more than security analytics although this continues to be an area the company is working on. Cervelli says companies are using data, not just to secure their businesses, but to also make more sense of changing environments as businesses move to an increasingly hybrid world.

By using data about what’s happening in their businesses, Cervelli says capturing data and correlating it allows businesses to make smarter decisions about what to do with their infrastructure.

In one sense, this is bringing Splunk back to their roots – collecting data from multiple sources and bringing it together. Over recent years, as the SIEM market has grown, Splunk has been seen a significant player in that space. But Cervelli says the company has never lost sight of that initial focus on bringing data to one place where it can be used intelligently.

“We went through a solid transformation a couple of years ago to add security as a revenue stream but we never really lost our focus on application delivery as well as infrastructure monitoring. They’re growing at a robust and healthy rate. We benefited from a ‘tail wind’ in security,” he said.

Cervelli added that the ‘novelty’ of security has captured lots of attention but that Splunk sees SIEM as just one use-case for the platform.

The company is focussed on five key areas; security, application development, IT operations, business analytics and IoT with about 40% of revenue coming from security, 40% from IT operations and the rest from the other areas. But the focus on data collection is what has helped businesses properly assess the risks and opportunities in the business rather than looking at just one specific application such as security.

“The data you would ingest for security is valuable for IT operations and application development”, he said. By applying a different lens to the same data you can gain different insights across the entire IT environment. A traditional SIEM may let you collect that data but it’s about using the data for multiple purposes.

Cervelli’s keynote was focused on the collection and use of machine data and how this changes the expectation of people and how they interact with different organisations. People are increasingly data rich but lack ways to effectively harness it. For example, outwardly simple transactions such as booking transport from a ride share service rely on and create massive amounts of data that can be harnessed in all sorts of ways.

He noted that during his address, he was able to build a map of people’s movements at the event by using the beaconing services that smartphones offer, when they weren’t directly connected to the access points on the conference network. By being able to collect that data and perform analytics on it, he said it was possible to create useful information that could inform business decisions.

For example, Monash University was able to use data from access points to get a better understanding of student movements, attendance and other data that allowed them to tune services such as security and catering.

Once companies are able to collate and harness the data they collect, it’s possible to use that data to power other elements of the business – not just information security and IT operations. Cervelli says it’s about making companies “one step smarter than they are today”. For example, while a function might be working well on average, how does the business know when something is operating outside reasonable bounds? Or can failure be predicted?

This is what is driving the use of machine learning, part of Splunk’s expanding product offering. This augment’s Splunk’s “secret sauce” – the collection and clean up of data from disparate sources. This is being used by telecommunications companies to predict cell tower failure, banks to detect and predict rogue traders as well as other different use-cases.

Cervelli said it’s these kinds of different applications that are duelling the companies growth – from 15 to 90 people in just a couple of years – locally.