Why File Analysis Tools are Crucial to Managing ROT Data

Too much of anything can be problematic. And the same is true in a network for redundant, obsolete, and trivial (ROT) data. It impedes productivity and desired outcomes, poses data security, legal, and compliance problems, and increases storage expenses. The good news is that by properly planning and investing in the correct file analysis tools, businesses may drastically reduce the disadvantages of ROT data and reap the benefits.

But what exactly is ROT data?

Simply described, redundant data is that data that is duplicated and kept in several locations within the same system or across multiple systems. Data that is obsolete is information that is erroneous, incomplete, or no longer in use. It may include out-of-date information that has been superseded by new information. Trivial data is information that does not add to corporate knowledge, business insight, or record-keeping obligations.

Many copies of an email saved in the system made by a sender by delivering it to multiple users are classic examples of redundant data. An example of obsolete data is old versions of outdated documents preserved in SharePoint. And the address of an employee who left the organization years ago may be regarded as both trivial information. And all of this is directly responsible for the issues that come up during unstructured data analytics.

What is the issue?

Keeping outdated personal information on a former employee or several copies of the same email may not appear to be a problem at first, but it is. Some severe concerns that emerge when businesses do not dispose of ROT data include the following.

Risks to data security

The more data you have in your databases and file servers, the more difficult it is to safeguard it. By removing the clutter using a file analysis tool, you can better understand your information and focus your security efforts.

Productivity losses

Employees lose time searching for relevant data amid the clutter or rectifying work they've already done with outdated data.

Incorrect judgments

Making decisions based on erroneous data analysis might result in negative consequences.

High storage costs

According to Veritas Global, as much as 33% of the data held by enterprises in 2016 was redundant, outdated, or trivial, with the remaining 52% classified as "black" data, the worth of which is unknown. According to Veritas, managing all that data would cost firms around the world $3.3 trillion by 2020. The expense of data management is directly proportional to the amount of data kept.

Legal risks

Having to filter through that ROT data without a robust [in-place file analysis solution]/file-analysis/) limits your capacity to react to legal e-discovery requests quickly and correctly.

Risks of noncompliance

Regulations such as GDPR and CCPA need careful tracking and disposal of customers' personally identifiable information (PII) and a privacy policy outlining how you gather, keep, and dispose of consumer data.

How can companies deal with ROT?

To manage ROT data, it is crucial to use the proper methods and file analysis tools for it. The measures below can help you significantly minimize the quantity of ROT data on your network:

• Make a taxonomy for your data that works. Collaborate with key stakeholders to develop a consistent set of definitions, labels, and groups so that you can readily comprehend the information you have.
• Create a policy and a set of best practices for dealing with ROT data. Establish mechanisms, for example, for removing outdated records and inconsequential data.
• For each category of information, establish a single source of truth (SSOT). This will reduce the confusion caused by versioning. The "correct" version is always the one saved at the SSOT location.
• Automate the above procedures using file analysis software, including defensible deletion, archiving, tagging, etc. This saves your workforce time spent on manual operations and reduces the possibility of human error.

Put an end to the spread of ROT

Keeping up with the proliferation of ROT data is a continuous activity, not a one-time occurrence. Therefore, investing in a powerful file analysis tool becomes a necessity. It assures correct data tagging, aids in automating critical information management processes, and enables strong information governance based on intelligent data review. This leads to:

• A thorough awareness of ROT data in your IT system allows for data minimization opportunities.
• A solid procedure for lowering the possibility of security concerns and the costs associated with a data breach.
• Simplified legal and regulatory compliance responsibilities.
• Increased productivity by making data more accessible.
• You can make better selections if you have exact search results.
• Reduced data storage and management costs.

Reach out to our experts here for more information on managing ROT data using file analysis tools.

Dark Data data analytics data management data processing data storage File Analysis File Analysis and Management file analytics file cleanup file management file shares information governance Information Management records management unstructured data management

Bivek Minj graduated from the Indian Institute of Mass Communication with a degree in English Journalism. He serves as a Content Writer at ZL Tech India's Marketing department. He comes to the industry with a desire to learn and grow.