Mar 25, 2021

Spectra StorCycle to digitise Imperial War Museum artefacts

Data Storage
Software
Technology
Sam Steers
2 min
Courtesy of Getty Images
The Imperial War Museum, working with Spectra Logic, is using data storage software to preserve its most valuable artefacts...

The Imperial War Museum in London is to deploy a software that will digitise its physical artefacts, following an announcement made yesterday.

Spectra StorCycle, designed by data storage company Spectra Logic, transforms historical assets into digital files which can be stored on the museum’s system. 

Ian Crawford, Chief Information Officer of the Imperial War Museum (IWM), said: “When we set out on our search to find a storage solution capable of preserving Imperial War Museums’ substantial digital archive, there were specific criteria on which we were not willing to compromise. 

“Spectra met all of our requirements and then some, and now continues to deliver with StorCycle’s storage lifecycle management capabilities.”

The Imperial War Museum has five sites across the UK - IWM London, IWM North, IWM Duxford, the Churchill War Rooms and HMS Belfast - and is home to 750,000 digital assets with that number constantly rising.

The move to digitise the artefacts, which include videotapes, audiotapes and photos, will prevent them from disintegrating, allowing them to continue to be shown to the public for years to come. 

The Spectra StorCycle functions by identifying and moving inactive data to a Perpetual Tier of storage.

Storcycle scans the IWM departments’ data storage for media files older than two years and more than 1GB, before moving them to the IWM archive. 

Talking of the importance of data storage, Vice President of Spectra Logic’s EMEA sales, Craig Bungay said: “IWM preserves invaluable historical data and it is vital that their data storage infrastructure be failsafe and reliable in addition to providing flexibility and affordability.”

Mr Bungay explains that this is achieved by “storing multiple copies of the museum’s data on different media” and by “automatically offloading inactive data from a primary storage to its archive solution using StorCycle.”

The Imperial War Museum (IWM) is reportedly on track to also benefit from cost-savings by digitising its artefacts, proving beneficial to the company in the long term. 

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Jun 23, 2021

How is AI helping to manage workloads in data centres?

AI
datacentres
Technology
WorkloadManagement
3 min
Artificial intelligence (AI) technology may be able to help manage workload tasks in data centres. Here’s how.

Workloads are taking their toll on the data centre industry, increasing to the point where enterprises are now turning to artificial intelligence (AI) technology for help in reducing the burden on IT teams while boosting efficiency and reducing costs. But how can AI help, and are data centre managers prepared to hand over the responsibility of managing tasks to machines? 

Management through automation 

One way in which artificial intelligence can help control data centre workload is through automating it to the most efficient infrastructure both inside the data centre itself and in a hybrid-cloud setting consisting of edge, cloud, and on-premise environments. 

If AI is used more in workload management, data centres in years to come will look different to those of today. The technology could see the creation of several smaller, interconnected edge data centres, all of which would be managed by a single administrator. 

Reducing costs is something that many, if not all, organisations in the industry are looking to do, mostly due to several factors keeping costs high, such as inflation, and pandemic-necessitated budget cuts, and tougher competition. Jeff Kavanaugh, Head of the Infosys Knowledge Institute, said: “AI and automation have proven to be powerful tools in workload management, as it frees employees from time-consuming and mundane tasks and allows them to focus on work that actually requires a human”.

Non-AI tools are reactive instead of proactive 

While many data centre managers already enlist the help of non-AI tools to manage tasks, the tools in question are often reactive instead of proactive, according to Sean Kenney, Director, Advisory at KPMG. “They react to the problems in the data centre, but they don't collect data to determine any foresight to reduce the problem behaviour”, he said.

Sanket Shah, a Clinical Assistant Professor of Biomedical and Health Information Sciences at the University of Illinois in Chicago, believes AI can also help managers who may struggle to predict their future plans and requirements. He said: “With AI, capacity and horsepower can be allocated in a more efficient manner, allowing organisations to scale and become flexible. Automating certain processes and shifting power where necessary will ultimately lower costs for those [managers] that have rapidly evolving data needs”.

However, the use of AI technology in data centres is not a new concept. In 2014, U.S tech giant Google announced that it was using AI technology it purchased from the AI specialist DeepMind to enhance its data centre equipment management across several sites. 

AI’s involvement in the data centre industry is ever increasing. Bill Howe, Associate Professor at The Information School of the University of Washington, highlights this, saying: "There are a tonne of choices and a tonne of limitations, but there are usually ways to mitigate those limitations. 

“I don't see the problem of choosing the right methods and engineering solutions ... to be particularly more or less challenging in workload management than any other complex AI application”, he said. 

It is clear that the use of AI technology in the industry is becoming more prominent. But what about its ability to replace humans? Richard Boyd, co-founder and Chief Executive Officer of artificial intelligence and machine learning developer, Tanjo, said: "Machines simply cannot replace humans in many respects, but there are certainly areas where machines are much better than humans.

He concluded that "popular opinion will shift once AI and ML become prevalent and workers adapt to this new partnership”.

 

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