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Big data, ML boosts IT service management

Staff Writer
By Staff Writer, ITWeb
Johannesburg, 26 Jan 2018
Understanding patterns from the past.
Understanding patterns from the past.

The features introduced by machine learning will add a tier of intelligent automation to traditional IT service desks.

"This will aid decision-making, enhancing staff productivity and opening up a level of smarter self-service for the end user," says Edward Carbutt, executive director at Marval Africa.

"The faster networks become, the more data is consumed and generated," says Carbutt. "In today's digital world, with its fast networks and constantly evolving technology, information is being accumulated at a rapid pace. This poses challenges for IT service management (ITSM) teams, who are inundated with enormous data streams, often too large to process manually. However, the application of machine learning to sift, sort, analyse and manage Big Data could help to simplify the tasks of ITSM."

Under pressure

He adds that traditional ITSM departments are constantly under pressure, as they have to deal with what he calls "Vs" of big data - volume, variety and velocity. ITSM receives enormous volumes of data, which is only compounded by the flood of data from Internet of things (IOT) devices, rendering effective sorting practically impossible.

Moreover, the types of data grow increasingly complex, as it is generated from a slew devices in a in a variety of ways. If you add to this the sheer velocity of data, it must be processed instantly or it is lost.

Carbutt says for ITSM teams, there is valuable information to be had from big data - information that once harnessed, improves operations and service delivery.

"There are two other "V's" of big data, lesser known although no less important," he adds, "Veracity and validity."

Veracity is the accuracy and integrity of data, where the true value and meaning lies - but also the biggest challenge. "Being able to extract the meaningful data from the unprocessed bulk of it is increasingly difficult to achieve. This is where machine learning proves invaluable."

Secondly, validity gives relevance to the data and works together with veracity. "The importance lies in the applicability of the data to reach the desired outcome. Though accuracy is imperative, organisations should still consider the 'age' of the data being used, as machine learning depends on the latest information provided."

Instant access

He says to imagine if an agent had instant, real-time access to a customer's information and solutions and was able to, at the click of a button, effectively address the demand or need of the customer. He says this is the power of data combined with machine learning capability - the ability to assist customers in real-time.

Machine learning allows IT staff to understand 'patterns' from the past and make predictions for the future from the large amounts of accumulated data. Although ITSM already makes use of intelligent computing, which collects an abundance of data, machine learning, when properly applied, automates the process of sorting through the data, identifying patterns and applying them to provide possible solutions to common issues.

"In an age where customer experience is a critical component of a business, the ability to answer requests with more accuracy, speed and precision becomes a differentiator," adds Carbutt. "Machine learning also enables a 'self-service' functionality that customers are able to leverage to resolve common issues. The automated process should relieve some of the pressure that ITSM departments feel - freeing up their time to focus on the more complex requirements."

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