Cluttering the cloud: Counting the cost of data landfill

by wrich
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By Stuart Bernard, VP Global Digital Solutions in EMEA at Iron Mountain

C-suite executives worldwide are under mounting pressure – not only to grow profits and shrink costs, but to make decisions that are socially and environmentally responsible. As public scrutiny increases, businesses are expected to deliver tangible sustainability enhancements throughout every facet of their operations.


And in a world where the volume and complexity of data they hold continues to swell, so does the impact of data storage – both on companies’ environmental performance and their bottom lines. This reality has brought the pursuit of more sustainable data management solutions far higher up the business agenda in recent years.

Growing hunger for a byte

On paper, cloud storage ticks several boxes – enabling organisations to securely store vast and rapidly expanding amounts of data off-premises for undetermined periods. These benefits, coupled with the increasingly stringent data protection legislation, have led to a huge surge in demand. 

Last year, Gartner predicted that by 2022, up to 60% of organisations will use external cloud services – double the 2018 figure.  And that was before the surge in remote working prompted by the COVID-19 pandemic served to convert many former cloud sceptics.

Unfortunately, however, our insatiable appetite for storage capacity comes at a cost. More data means more data centres, which – according to a recent study from the academic journal Science – already account for one percent of all electricity consumed worldwide.  Beyond concerns over carbon footprint, there are also very real operational risks. 

The cloud conundrum 

Today’s norm has become multiple sources of data creation, spread across multiple cloud vendors and stored across multiple platforms, creating an – at best – highly complex, and – at worst – extremely inefficient multi-cloud data management conundrum. 

Whilst concerns over data privacy and security have long dominated the CIO agenda, the issue of what we call ‘data landfill’ has been largely ignored. Individuals and businesses have become so used to entrusting their files to ‘the cloud’, that most organisations are unaware of how many terabytes of unnecessary data they are storing, not to mention the financial and environmental cost. 

Contrary to popular opinion, cloud storage is far from virtual. In addition to the cost of housing, powering and cooling these vast brick and mortar facilities, the physical media on which the data are stored all takes up space. 

The silver lining

So, what can organizations do to minimise their contribution to data landfill and get both their carbon and data footprints under control?

  • Take a proactive stance on data management

With data volumes poised to mushroom and companies increasingly adopting multi-cloud environments, it is vital they come to grips with data management — accounting for privacy, compliance, and security issues, while ensuring data is accessible to the business. This includes understanding different types of data, and where and how to store and migrate them.

  • Develop a robust data tiering system

To ‘tier’ data means classifying the information held by your organisation – based on its relative urgency, importance and lifecycle stage – and matching it with the most appropriate storage solution: on premise, cloud or multi cloud. This exercise often yields a substantial ‘grey area’ – records you probably won’t need but prefer not to lose. Such materials are often more cheaply and sustainably stored offline. Data tiering offers two main advantages. First, using the most expensive storage only for applications that need it saves money by allowing lower-cost options for the rest. Secondly, tiering cuts capital expenses by extending the life of expensive hardware. It can also reduce operating expenses by lowering the costs of managing and maintaining high-performance drives.

  • Automate your content management

Like any other manual process, manually archiving data is a labour-intensive process – particularly given how data grows exponentially over time. It is also prone to human error, such as being moved to the wrong storage tier or prematurely purged. An upfront investment in data lifecycle automation software can save a substantial amount of money in the future in the form of labour costs and, potentially, in the avoidance of fines for compliance violations.

  • Pay only for the data that is necessary

The pricing structure used by many vendors can make data storage costs both inefficient and unpredictable. Many data management services require payment for ‘planned’ or ‘allocated’ capacity, which results in companies paying for storage space they don’t need. The issue is further compounded by the escalating costs of data protection. For every terabyte a business stores, there are typically two terabytes of data protection (at least 1-2 backup copies). If these are stored online and charged on capacity basis, it can result in you paying to protect a great deal of data unnecessarily. For maximum efficiencies, look for partners that can support you in streamlining this process, and only charge you for the space you use, without additional fees to access or move data.

  • Leverage AI and Machine Learning to enhance your use of data

Most organisations recognise the potential of their data but struggle to unlock the power within because they have too much unstructured and unclassified information, lack the internal resources and skills to analyse it, or both. Fortunately, however, digital technologies offer new opportunities to make better use of your data. Machine Learning, a subset of AI, uses algorithms to scour information and identify patterns they aren’t purposefully programmed to find. They work with data sets that are too large for humans and can create structure where none exists. The software can scour data to apply proper retention strategies, as well as unearth new revenue streams and cost saving opportunities.

Data landfill is a very real and growing issue, with direct financial and environmental implications. But it is challenging for companies to manage effectively internally, often leading them to engage managed services providers. 

For optimum results, it is critical that companies that decide to outsource, delegate – rather than abdicate – the responsibility to safely and sustainably streamline their data storage.  The right vendor will help shape a data management strategy that fits across the entire data lifecycle, while ensuring accessibility, security and cost effectiveness, as well as transparency on environmental performance.





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