UK companies are markedly less willing than their US counterparts to seek out and embrace new techniques for managing archived data over the long term, possibly reflecting lower awareness in the UK of compliance and retention issues, according to new statistics from the second annual BridgeHead Software Information Lifecycle Management (ILM) Audit.
Striking national differences are apparent in responses to the value of maintaining long-term archived data. Sixty two per cent of US respondents rate preserving archived data for the long-term on multiple media types such as disk, tape and optical technologies as important or very important, while only 41% of UK respondents feel the same way.
UK apathy also registers at the other end of the scale where 20% of UK respondents answer 'don't know' (6% in the US) and 16% answer 'unimportant' (11% in the US).
And, when asked about the prospect of being able to keep multiple copies of long-term archived data in multiple locations, US respondents are, again, significantly more open than their UK counterparts: just 51% of UK respondents say this would be 'important' or 'very important' compared to 69% of US respondents.
Responses from both countries provide a near-identical pattern of data retention requirements: 9% of respondents identify that some of their archive data will need to be retained for in excess of 30 years, with a total of a third of UK respondents (and 37% in the USA) saying in excess of ten years. Twenty seven per cent of UK respondents and 31% of US respondents, say the longest that any data in their organisation needs to be retained is four years or less.
When asked how valuable it would be to be able to search all archived data based on content, only 51% of UK respondents say 'important' or 'very important', compared to 61% in the US. In both countries, more than a fifth didn't know if it was important or not.
Information lifecycle management or "ILM" has come to be accepted as a critical business process to ensure cost-effective and safe management of information. However, ILM requires an entire organisation to be highly disciplined and involved in the classification and prioritisation of information so that IT departments can correctly manage underlying data. With growing data volumes, disorderly data classification by user communities and other departments, and compliance requirements to be able to search for particular data in an archive, IT organisations are beginning to focus on what they can control: Data Lifecycle Management or "DLM".
DLM automates and optimises data placement and management techniques used for data throughout its lifecycle. It operates on what is already known about data from its attributes, and from textual or other analytically induced content. Policies can be created based on the resulting data classification that automate the repositioning of data and correctly apply other data management rules. These policies create the appropriate number of spare data copies to ensure data protection, business continuance, long-term retention and compliance.