Centralized Discovery
A centralized metadata catalog for unstructured data allows users to easily search for and understand data assets across the enterprise, bringing structure to these datasets across storage silos. This not only allows IT to locate sensitive and protected data quickly to avoid data leakage and mishandling, but it allows any authorized user to find the files that they need quickly for their projects. In the age of AI, this searchability and identification of required datasets is pivotal to gaining a competitive advantage.
Real-Time Monitoring and Mitigation
Automated tools and processes help IT and cybersecurity teams monitor data quality and changes in real time, as data is constantly on the move and in transformation. IT needs ways to automatically scan for PII, for instance, and confine it if it is discovered in an insecure or noncompliant location.
Ransomware Protection
The ability to identify, tag, and continuously move “cold data” that hasn’t been accessed in a year or longer is a huge advantage, because it reduces the overall attack surface by automatically tiering it to an object-locked storage location, such as Azure Blob or AWS S3. Now, the cold data can’t be modified or accessed by cybercriminals, and IT can deploy its strongest anti-ransomware protection on high-priority, active data. An unstructured data management strategy aligned with a ransomware protection strategy not only reduces risk, it can dramatically decrease costs.
Getting Started With Metadata Management for File and Objects Storage
The first step in mining unstructured metadata for compliance needs is to get visibility into all metadata across file and object storage. An unstructured data management solution can index and organize this metadata rapidly to show initial trends, such as amount of data in storage, growth rates of data, amount of rarely accessed data, and orphaned or duplicate data.
Standardization also plays a big role. A consistent tagging taxonomy or catalog ensures that teams across projects and storage environments apply the same definitions. Deciding whether to tag at the directory or file level is another key consideration. Directory-level tagging is far easier to manage since it reduces the overall tag volume, but it requires careful oversight to avoid misclassifying files that don’t belong.
Custom metadata enrichment is where organizations can add real value. By tagging files with dimensions such as project or PII, data owners support precise queries and more powerful analytics downstream. Collaboration is crucial here: IT can manage the infrastructure, but accurate tagging depends on input from the scientists, researchers, or business users who understand the data itself.
Automation is the only way to handle the sheer scale and complexity of modern metadata. Unstructured data management platforms and catalog tools can apply, track, and persist metadata across hybrid environments, far beyond what native storage systems can support. These platforms can automate workflows to continuously find and move protected data from the wrong locations and in accordance with internal policies and industry regulations.
An iterative, systematic metadata management program for structured and unstructured data can reduce risk in a time when threats are proliferating and make all enterprise data more discoverable and useful for IT and departments alike.