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The uncontrolled growth of unstructured data presents potential vulnerabilities for brand damage, corporate liability, and fines.
Not only the GDPR demands that companies know where the important and sensitive data actually lie. But the mass of unstructured data is distributed uncontrollably via the file system and warehouset themselves in deeply nested directories. Resolving this contradiction is a declared goal when it comes to analyzing file server data.
Make better informed decisions faster with data-driven intelligence
Powered by advanced artificial intelligence and analyzed migRaven.Analyzer continuously sensitive and other valuable data – at scale. Er discovers a variety of aspects of your unstructured data, including age, type, last access, location, access permissions, internal and external sharing rights, and more.
What you should know about your company data
- Where are they?
- How old are they?
- When were they last changed?
- Who has access to it?
- Who can make binding decisions regarding the data? (data owner)
- Are they subject to special retention requirements?
- How important are they?
- Are they right on the company server?
With various reports on authorization depth, data usage, obsolete data, and much more. allows migRaven deep insights into the state of your data and rights structure.
Who is an administrator or Data owner (data owner) here Perspective or just one Overview wants to get, will be ready with the by the operating system asked On-board resources do not get any further. But transparency is absolutely necessary in order to understand data structures and ultimately to restructure them.
Obsolete data limits the work of all users
For example, administrators would like to know which data is really still needed and which only causes costs on the storage space and unnecessarily lengthens the backup.
But backup costs are marginal when compared to the calculated loss due to the ubiquitous inefficiency of handling the file system.
The mass of useless data prevents an unobstructed view of the files actually needed, causing errors and time delays. This affects all users in their daily work and causes employees of large organizations to spend an average of 30 - 60 minutes per day (!) Searching for files or to work with old and wrong files.
On average, 60 - 80% of all data in the large enterprise file system is outdated, obsolete or simply wrong. For the user much worse: on every employee Tens of thousands of files come in hundreds of folders and subfolders. Anyone manually deleting some files here can give up directly.
migRaven's Tree View: Breakdown of the file age ...
... or differentiated by file types.
Of course, structural analysis does not just concern the location of data. Also connections like here between data age and file type are valuable information, which make a subsequent cleansing of these data structures possible.
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