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According to IDC (International Data Corporation), the world will store 175ZB of data by 2025, more than five times the 33ZB of data stored in 2018. Much of that data storing will likely be data hoarding, which has always been a significant IT concern and has rampantly increased since the pandemic outbreak, as millions work from home.
According to a Veritas Databerg report, 32 per cent of data stored by organisations is junk. Junk data includes non-business, duplicate, stale and unused data left behind by former employees. Organisations spend exorbitantly on data storage mostly because of mismanagement. In most of the companies, IT admins do not even have information on where employees save their files, both personal and professional.
This understanding is important to take precautionary steps to identify and protect sensitive data. Lack of information might not just put the organisation’s security at risk but might also prolong the process of identifying vulnerable data, which could be a potential threat.
Role of file analysis
File analysis can be a game changer in helping organisations optimise their data storage and enhance their performance capabilities. Adopting an effective file analysis tool can help them address important risks that mismanagement of data might otherwise raise.
Like cracks in a building, these risks can gradually cause serious damage to the operational structure. This article aims to educate CIOs, entrepreneurs, IT heads, and employees on the four key benefits that a robust analysis tool can offer in managing data.
Optimise data storage : Managing data effectively can help organisations use their storage capacity to the optimum. For instance, the same document might have five different, duplicate versions that might be occupying space without a purpose.
Analysis can help admins easily identify such data and retain only the original version. This will also help employees identify the right data immediately without wasting their time.
Improve data efficiency : File analysis helps organisations steer clear of redundant, obsolete, and trivial (ROT) data. Redundant data includes duplicate and obsolete files, with old/stale data that has not been managed. Trivial data comprises personal files saved by employees.
Analysis helps maintain real-time updates on data and segregate data based on the frequency of usage, the owners of a particular folder, and external parties who have access to this data. Analysis-driven insights will help the data administrators clear ROT data from their repository.
Cost optimisation: The cost of buying storage is high and usually organisations spend millions in just acquiring storage space. Given the significant investment, it is important to ensure that the money is spent wisely. As per ManageEngine estimates, a mid-size organisation storing 5TB of data can save approximately $3,500 a year by spending around $1,000 on analysis. With 10TB of data, it can save about $20,000 a year by spending approximately $2,000 on analysis. Optimising data storage has helped companies cut down costs dramatically.
Mitigating security risks through real-time analysis : Security is one of the biggest IT concerns for organisations, especially those in banking, retail, and healthcare sectors. It is critical for organisations to ensure that either files created by former employees are deleted or the ownership of those files is shifted to a current employees to minimise the risk of unwarranted accesses and privilege abuse.
Managing data helps understand where information is stored. It also helps identify ransomware and other malware-corrupted files before any damage occurs. Through file analysis, the IT team can keep an eye on who has access to such privileged data and take actions real-time in the event of any unknown log-in.
Better management
For any business to continue its operations, data management can no longer be an option. It has become a prerequisite. This is even more pressing in the current scenario when organisations are looking at a hybrid model of working. It is imperative for companies to prioritise data analysis and have a better understanding of the data repository they own.
This clarity will help the leadership teams make better and faster decisions and help IT teams identify vulnerable data and remove duplications.
The writer is Product Manager, ManageEngine
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