Enterprise data is growing exponentially. For global organisations, managing, storing and accessing that data is a constant and costly challenge. Here we look at strategies for protecting global organisations against data loss and non-compliance.
Is data a growing problem?
From supporting Big Data initiatives and testing applications, to simply managing peaks and troughs, enterprise data needs are constantly evolving and require the storage to support growth in an efficient and cost-effective way. This is putting increasing pressure on legacy data centre infrastructure, which is largely self-owned and requires constant maintenance, expensive upgrades and continual investment as businesses expand globally and workforces become mobile.
The need to store increasing amounts of data is pushing the amount of investment needed. Forrester Forrsights surveys monitoring IT spend on data storage over the past six years reveal that, while in 2007 10 per cent of IT budgets were attributed to storage, this figure had already risen to 17 per cent by 20101.
As stored data increases, so does the issue of its security. Data is arriving from disparate, widespread sources and possibly stored wherever there is capacity available at the time. This raises an element of doubt about whether the infrastructure, where data resides, meets the necessary security and compliance requirements. There is also the issue of employees compromising data security by sharing passwords and files. A study by Cisco revealed that 25 per cent of employees share their passwords with co-workers2, while 46% transfer files between their work and personal computers. Add to that the requirement for organisations to retain data for an average of seven years and it becomes clear that storage and file-sharing poses a serious potential risk to enterprises and must be part of business continuity and disaster recovery plans.
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3 tips for reducing the risk and cost of data
1) Establish a data lifecycle management policy – categorise data according to its importance and value, and how frequently it needs to be accessed. Some data may lose its importance with time, and is only required for record-keeping or compliance reasons; it will rarely be accessed and can be stored in a deep archive. Other data, such as applications and databases, should be considered as primary data, and readily accessible. There may be a third category between the two: near-line archive, for data which is not instantly required but will nevertheless be accessed regularly.
2) Tier your data – this helps reduce storage costs by storing data according to its importance and how frequently it needs to be accessed. Primary data, which is used constantly and therefore needs to be accessed instantly, is stored on Tier 1 – the fastest, most available and robust tier (which is usually the most expensive). Data that is required less frequently can be tiered down to slower, cheaper Tier 2 Near-Line Archive or possibly out to Tier 3 Deep Archive, which might use CD or tape storage. Typically, Tier 3 data will be call recordings stored for long-term compliance.
3) Consider buy vs. build – Buying-in storage is considerably more cost-effective and agile, as it offers the scalability to deal more easily with varying and unpredicted rates of data growth. Buying-in eliminates capex and moves to a utility pricing model, with more predictable operating expenditure and a lower total cost of ownership. It also provides the flexibility to grow or even scale back your capacity in line with the organisation’s actual data storage needs, eliminating the wastage of over-provisioning. Additionally, buying-in a consolidated storage service shifts much of the management burden from the organisation’s IT people to the provider, who would also be responsible for backup and disaster recovery.
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Enterprises that regularly review their data storage can improve their storage utilisation by at least 20%.