While day-to-day operations themselves generate ever-increasing amounts of data, the challenge is compounded by what’s been dubbed ‘data hoarding’. This occurs when staff members retain data that is no longer required or keep multiple copies of the same file in different locations. This could also occur when employees store personal data or data that is irrelevant to official purposes in corporate data stores.
As data volume in an organisation grows, avoiding hoarding becomes increasingly difficult. IT teams can find themselves bogged down by the management task, diverting time, and resources from other projects that add more value.
The types of data that cause many of the issues can be categorised by the acronym ROT—redundant, obsolete, or trivial data. One of the primary issues that flows from having ROT data is the cost of providing ever-growing storage capacity across an organisation.
As the amount of storage capacity is increased, there is a rising impact on the performance of the infrastructure. If you want to store large amounts of data, you have to compromise on performance. Otherwise, costs will spiral and consume an ever-greater proportion of the overall IT budget.
A second issue arises around data security. When large volumes of data are stored and copied across multiple locations, sensitive data may end up in an insecure place. As data volumes grow, spotting problems like this becomes an increasingly difficult task.
The role of file analysis
A strategy adopted by growing numbers of organisations is the deployment of a new breed of file analysis tools. These tools, increasingly incorporating artificial intelligence (AI) capabilities, can automate much of the management burden and keep data hoarding under control.
File analysis tools can assist in a variety of ways, including:
- Reclaiming data storage capacity: The tools can be configured to examine all data stores and identify files that fall into the ROT category. Duplicate files can be automatically deleted while the master copy is retained. Any that require human evaluation can be shifted to a different location for further analysis.
- Optimisation of disk space: An effective file analysis tool can monitor disk space usage across an organisation and alert the IT team if free space falls below a predefined limit. This allows preemptive management steps to be taken before there is an impact on performance.
- Metadata analysis: The tools can automatically analyse the metadata associated with stored files and determine whether they are still relevant or can be either archived or deleted. This reduces the workload on infrastructure managers and lowers operational costs.
- Storage pattern analysis: The tools can monitor and analyse data storage patterns and space consumption rates by users over time. A baseline of normal usage can be established, and the tool can then flag any anomalies and take necessary remedial actions. File analysis tools can provide impressive results when combined with AI and ML capabilities.
- Permission analysis: Sometimes files end up being made available more widely than is required. The file analysis tool can assess how often and by whom files are being accessed and determine whether that access should be reduced to a smaller number of staff.
Effective deployment of file analysis tools can have a significant positive impact on how data is managed across an organisation. Once in place, the return on investment that will be achieved with the tools rises exponentially as the volume of data being stored grows.
By taking time today to carefully evaluate their existing data infrastructure and deploy a suitable analysis tool, organisations can be much better placed to manage the ongoing increases in data volumes that will continue to occur in the future.