How to meet the 2020s data management challenge

, Jan 8, 2021

By Mark Benson

The 2020s is the decade of data management

As the importance of data as a corporate asset grows, data management becomes ever more critical. Data is the new oil, not just in terms of its value, but as the vital fuel for AI and the other core elements of digital business.   

Even before the extraordinary events of 2020, data management was a rapidly growing challenge for many enterprises. Managing data costs, maintaining control of data held across multiple silos, dealing with data in the cloud and keeping up with the constant demand to do more with that data, more quickly, were high on business agendas.

2020 and its aftermath throws these challenges into even greater focus.

Sweating data assets will be key in the constrained economic environment ahead, especially when, for example, restrictions inhibit the ability to get new infrastructure into data centres.  

Enforced changes in working methods have left businesses to readdress their resilience, remote working and event readiness practices, all processes where effective data management is front and centre.

Each enterprise is at its own point on the data management journey. The key now is to understand what that point is and set out the path for where to go next.

This blog, with the recent Logicalis/IBM fireside chat, shares some ideas and pointers on where that journey should be headed.

The virtual storage revolution 

Twenty years ago, if you were implementing a new business application, you’d likely buy a new physical server to run it. Then VMware and the rest came along, and we’ve never looked back; the inflexibility and long lead times of a non-virtualised server environment are largely in the past.

Just as server virtualisation delivered exponential improvements in applications infrastructure management, storage virtualisation is doing the same for data management, with IBM at the forefront.

Through a single API, IBM Spectrum Virtualise enables seamless, software defined, platform agnostic data management across on-prem and cloud platforms. Challenges around data lifecycle management, reduction and encryption are centralised into a single point of control, removing the constraints of a silo-based, physical data environment.

Pay per use data 

Storage virtualisation offers the flexibility to adapt to client storage needs. By automating tiering, block storage and volume allocation it enables fairer, usage-based charging regardless of whether the storage is on-prem or in the cloud.

Harnessing the potential of cloud data

Talking about seamless data management across cloud and on-prem at your fingertips may sound like standard marketing hype, but if you’ve ever had to run DR from a cloud instance without it, you probably realise the practical potential.

By taking away most of the overheads of maintaining and accessing back-up data, storage virtualisation not only eliminates a lot of the angst around DR, it opens up the potential to exploit that data more fully, such as rapid access to near-live data copies as a boon for application developers.   

Securing data assets

A centrally managed virtualised DR environment enables a robust solution to the ‘recover’ component of a ‘protect, detect and recover’ cybersecurity approach.

Immutable, WORM (Write Only Read Many) and air gapped data storage, including state of the art tape solutions are all elements of IBM’s virtualised storage environment, assuring the ability to recover from ransomware attack. 

Dual-key capability which prevents any single individual, even an administrator, from being able to alter or destroy data, protects against growing insider and coercion threats.  

In the ‘detect’ space, storage virtualisation opens up the ability to apply powerful telemetry and analytics across the whole on-prem and cloud data estate. The IBM platform offers a comprehensive, turnkey service from detecting abnormal IO levels on a disk to building up shareable data on attack vectors and patterns.   

The totally portable data management platform

Virtualised data management has to be operable across any combination of platforms to be useful in a hybrid cloud world.

IBM has invested heavily in containerisation and orchestration capabilities so that its virtual data management platform already supports over 450 different platforms. It supports a multi cloud strategy aligned closely with cloud provider value propositions, scalable through Spectrum Scale.  

Where next?   

Taking the next step on the data management journey is about much more than just investing in a new product set.

First, you need to understand where your organisation is on that journey, and the particular opportunities, risks and costs it faces depending on its data management investment decisions.

Logicalis UK, working with IBM, offer a low touch study tool to drive that understanding. Using it is a consultative process, it’s not just a report, and it gives a comprehensive TCO assessment for data management in your organisation. 

If you’d like to learn more, contact us at

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