FEATURE DATA CENTRE MANAGEMENT


DATA CENTRES NEED TO DIFFERENTIATE TO SURVIVE


Organisations are looking to find patterns within their data that can deliver greater business and customer intelligence and predict future trends. Gartner highlights that the number of enterprises implementing Artificial Intelligence (AI) tripled in the space of a year. More than 30 per cent of data centres, however, that don’t deploy AI and machine learning won’t be operationally and economically feasible by 2020. Peter Ruffley, chairman at Zizo, discusses how we can best use AI and what its role is within the data centre


T


here is a growing need to dispel some of the myths surrounding the


capabilities of AI and data led applications, which often sit within the c-suite, that investment will give them the equivalent of the ship’s computer from Star Trek, or the answer to the question ‘how can I grow the business?’ As part of any AI strategy, it’s imperative that businesses, from the board down, have a true understanding of the use cases of AI and where the value lies. If there is a clear business need and an


outcome in mind then AI can be the right tool. But it won’t do everything for you – the bulk of the work still has to be done somewhere, either in the machine learning or data preparation phase. With IoT, many organisations are chasing


the mythical concept of ‘let’s have every device under management’. But why? All they are doing is creating an overwhelming amount of low value data. There’s no strategy there. The ‘everyone stores everything’ mentality needs to change. One of the main barriers to


implementing AI is the challenges in the availability and preparation of data. A business cannot become data driven if it doesn’t understand the information it has. With many organisations still on the


starting blocks, or having not yet entirely finished their journey to become data driven, there appears to be a misplaced


6 JUNE 2020 | ELECTRICAL ENGINEERING


assumption that they can quickly and easily leap from being in the process of preparing their data to implementing AI and ML, which realistically, won’t work. To successfully step into the world of AI, businesses need to firstly ensure the data they are using is good enough. Over the coming years, we are going to


see a huge investment in large scale and High-Performance Computing (HPC) being installed within organisations to support data analytics and AI. At the same time, there will be an onus on data centre providers to be able to provide these systems without necessarily understanding the infrastructure that’s required to deliver or get value from them. AI solutions are currently very resource heavy. Solutions to improve the performance of


large scale application systems are being created, whether that’s by getting better processes, hardware or reducing the cost to run them through improved cooling or heat exchange systems. But data centre providers have to be able to combine these infrastructure elements with a deeper understanding of business processes. This is something very few providers, as well as Managed Service Providers (MSPs) and Cloud Service Providers (CSPs) are currently doing. It’s easy to go down the route of promoting that ‘we can save you X, Y, Z’ but it means more to be able to say ‘what we can achieve with AI is..X, Y, Z’.


Data centre providers need to move away from trying to win customers over based solely on monetary terms. When it comes to AI, there has to be


an understanding of what the whole strategic vision is and looking at where value can be delivered and how a return on investment (ROI) is achieved. What needs to happen is for data centre providers to work towards educating customers on what can be done to get quick wins. Sustainability is high on the business


agenda and is something providers need to take into consideration. By sharing data between industries and working together to analyse it, the infrastructure needed for emerging technologies can work better. The hard bit is convincing people to relinquish control of their data by considering how much power and kilowatts are being used and how this is helping their social corporate responsibility. The appetite for AI is undoubtedly


there, but for it to be deployed at scale and for enterprises to see value, ROI and new business opportunities from it, data centres need to move the conversation on, work together and individually utilise AI in the best way possible or risk losing out to the competition.


/ ELECTRICALENGINEERING Zizo


zizo.co.uk


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