Mastering ROT Data Minimization: The Automation Blueprint for Enterprises

1. Discover Shadow & Native Data Across Clouds

Around 40% to 90% of enterprise data is “Shadow Data”, which includes ROT data. Securiti helps organizations inventory both native and shadow environments, providing a holistic view of their data landscape, including where sensitive and regulated information may be stored.

With its “Assets Discovery” functionality, Securiti continuously scans these environments to uncover hidden “shadow” assets and cloud-native data stores. Mapping out every data repository, from containers to file shares, ensures that no shadow or unmanaged dataset remains overlooked. By providing deep intelligence into its discovery, Securiti provides a holistic view of both known and unknown data repositories. This comprehensive visibility is crucial in identifying and tackling ROT data.

2. Centralize Data Inventory Across Hybrid Multi-Clouds & SaaS

Modern enterprises increasingly rely on a complex ecosystem of data sources–making it tough to keep track of where the data exists, limiting visibility on how it is used. Securiti addresses this by centrally cataloging all structured and unstructured data systems across hybrid, multicloud, and SaaS environments.

Securiti’s functionality flags ROT data for deletion or retention updates once its purpose is fulfilled by data mapping ties each asset and process to the right regulatory requirements, ensuring organizations understand which datasets fall under specific provisions of laws and frameworks like GDPR, CPRA, PCI, SOC 2, ISO 27001, or SOX. This unified perspective simplifies governance and links each dataset to the correct regulatory requirements.

3. Flag Obsolete Data Based On Age & Activity Criteria

Vast amounts of data remain untouched over time, offering no operational value. Securiti’s contextual data intelligence identifies files and datasets created before a certain date or that have remained unmodified for a specific period. This approach retires outdated data, reducing enterprise overhead.

By enforcing time-based and activity-based policies, Securiti pinpoints stale or outdated assets, enabling organizations to confidently retire them, which mitigates the likelihood of breaches with fewer idle assets in the environment, resulting in a more secure data footprint.

4. Detect Redundant Data by Identifying Duplicate Content

A large portion of ROT Data within an enterprise stems from redundant copies. Over time, employees frequently create multiple versions of the same document or store them in multiple repositories, resulting in data duplication that inflates storage costs and complicates data governance.

Securiti addresses this with advanced cluster analysis, which swiftly detects exact duplicates and near duplicates across diverse environments and minimizes the volume of redundant data.

5. Classify Sensitive Data to Identify Data Retention Violations

Once data is flagged as redundant or obsolete, the next crucial step is determining which files contain sensitive or regulated content and require higher-priority attention. From a compliance perspective, enterprises must ensure their data retention policies align with regulations like GDPR or CPRA.

Classification plays a pivotal role here: by scanning and labeling the nature of each file’s content, Securiti reveals whether it involves sensitive company-confidential information, financial identifiers, or regulated personal data subject to frameworks like GDPR, CPRA, or PCI DSS.

Securiti leverages advanced, AI-powered classifiers to detect sensitive data elements rapidly across complex, hybrid data landscapes. By identifying exactly which ROT files contain regulated information and determining that it poses genuine compliance and regulatory risk, Securiti empowers organizations to align remediation efforts with strict retention guidelines.

6. Eliminate ROT Data with Federated Auto-Remediation Policies

By centrally defining conditional policies, organizations can specify clear criteria for identifying ROT data—for instance, flagging files that contain sensitive financial documents stored beyond their retention periods. Once these files are detected, Securiti’s automated remediation takes over, providing several actions:

1. Alerting File Owners: The solution locates the file’s owner and sends an alert—either through Slack, ServiceNow, Jira, or another preferred collaboration tool—so they can review the flagged data.
2. Quarantining High-Risk Files: Administrators can temporarily move suspicious files into quarantine to minimize risk and prevent unauthorized access while waiting for the owner’s decision.

Throughout the process, detailed reporting and exportable results enable stakeholders to verify remediation efforts, support compliance reviews, and maintain thorough governance records. This policy-driven framework ensures consistent, timely, and fully aligned ROT data minimization with regulatory mandates while delivering granular insights into the evolving data landscape.

Best Practices & Tips from Real Data Minimization Projects

Enterprises often approach ROT Data minimization with different priorities and constraints. Securiti’s step-by-step approach ensures comprehensive coverage, yet some organizations customize it to focus on securing their most critical data assets first, according to their specific risk priorities and compliance demands.

Below are practical insights derived from real-world ROT Data minimization projects that illustrate how organizations can adapt these steps to their immediate needs:

1. Focusing Minimization Efforts on Urgent Compliance Requirements

In some scenarios, an organization may have a clear priority—for example, meeting PCI data retention guidelines within a known credit card processing system. Since that system is already identified, the enterprise can immediately begin flagging and remediating ROT data (Steps 3–6) without first discovering shadow data (Step 1) or building a comprehensive inventory (Step 2).

By addressing the most pressing compliance obligations first, teams can quickly mitigate risk and meet regulatory requirements. Once this immediate need is resolved, they can expand their data minimization efforts to other systems and environments as needed.

2. Using Sensitive Data Insights to Guide Remediation Decisions

Comprehensive scanning for sensitive data (Step 5) can be both resource-intensive and time-consuming. To optimize efforts, many organizations limit scans to the most critical or highly regulated systems first, allowing them to gain vital remediation insights without incurring the full cost of scanning everything.

Moreover, stale data with no sensitive content can be confidently deleted, freeing capacity and minimizing security and compliance risks.

By tailoring each phase—whether by skipping non-essential steps initially or focusing on high-impact data stores—enterprises can address pressing compliance mandates without delaying the broader, long-term goal of organization-wide ROT data minimization. Over time, these incremental wins build momentum and enable a more comprehensive solution that aligns with evolving business priorities and regulatory requirements.

Transforming ROT Data into a Strategic Advantage with Securiti

With Securiti, enterprises ensure a streamlined, compliant, and secure data environment. This proactive approach to ROT data minimization not only saves costs and reduces risk but also enhances data quality, enabling more reliable analytics, AI insights, and strategic decisions. In short, Securiti turns ROT data from a persistent liability into a manageable component of modern data governance.