The volume of data on most enterprise file systems has been growing at a rate of about 20-40% per year.
Along with Energy costs and Administrative expenses the effort required for the necessary Data Management faster every year.
The proportion of redundant, obsolete and trivial data, known as ROT data for short, is growing. An ever smaller proportion of all data is still needed, but it is precisely this important data that gets lost in complex structures among a lot of legacy data.
Wherever current files should actually be, these mountains of old data are piling up. They clog up directories, complicate administration, disrupt users' work and slow down backups.
Specifically, on average 50% of all data archived immediately and more 30% deleted directly which would significantly reduce the data storage costs in one fell swoop. But how can old and new data be separated from one another in such a complex directory structure?
There is only one direction in the data stock: the direction upwards. More precisely, it is an exponential growth and that in turn clearly implies: The problem will not solve itself.
Data is not stored in an orderly and structured manner, not like in Tetris, where the oldest is at the bottom and disappears at some point. No, it is no coincidence that unstructured data has exactly the same name: It is often stored in swelling directory structures in deep directories. And they clog the system to the point of collapse.
And even worse: the mountain of data is not only tending to become less valuable because data is less available. The data chaos also confuses the employees at work and costs up to 60 minutes of working time every day. So useless data not only loses its value, it becomes annoying data spam and needs to be sorted out.
Similar to what happened recently in the pandemic, every company must at some point break the growth in the area of unstructured data like a wave of infections. The longer you wait with effective measures, the more complex, strenuous and expensive it becomes in the end.
Obsolete Data Report for the analysis of mostly obsolete data structures
The Best Practice Report shows structural errors in the authorizations.
Our preview of migRaven.one Obsolete data is identified directly by the data owner.
No new share will change the chaos and sheer size of your data structures. And a migration to Sharepoint will not solve this problem either. Imagine an apartment that is slowly becoming full of rubbish because no one has ever taken anything down to the basement or to the bulky waste bin. You certainly won't put the old junk into new cupboards to bring order back. No, the old junk has to go, that's clear. And first of all! With this simple principle, your tidying up project will be a success.
With regard to the file server, it is therefore very important to first remove old data and structures, as we do as standard with our migration solution migRaven.one implement. We recommend a selection process that involves the departments or data owners in order to find outdated data. This task varies in complexity depending on the size of the file system and can be greatly simplified by a task management system.
If the productive and old data are separated from each other, you can design an optimal new data structure and actually focus on the current data. At the end, you only have to transfer it to the new structure. If necessary, old data can be made available in an archive, as we do with migRaven Data Retention, for example.
Our experts, with experience from numerous IT projects, will explore current topics related to security and efficiency in data usage, fundamental IT security issues, and data and permissions migration. Register now for free!
Webinar recording: Why AI fails without context – and how migRaven.MAX
Our experts with experience from many IT projects examine current topics related to security and efficiency in data usage, fundamental questions
Webinar recording: Why AI fails without context – and how migRaven.MAX makes concrete risks visible. Modern IT infrastructures generate large amounts of
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