ROT Data Minimization

The modern data landscape involves several data sources, including public cloud, private cloud, on-premises systems, and SaaS applications. Because of the growing volume of data sources, it has become increasingly challenging to create a comprehensive inventory. Most of the time, redundant, obsolete, and trivial (ROT) data builds up silently in these environments. According to Deloitte, “Data volumes continue to rise across all functions, without much regard for prioritizing what data must be maintained.” This enormous volume of stale data often goes unnoticed, losing its business value over time and consuming resources while creating liabilities.

If ROT data is not effectively minimized, it could cost enterprises millions of dollars globally. The money that could go into business intelligence and innovation is diverted to storage and backup overhead. Apart from the financial aspect, the accumulation of ROT data also increases the risks of compliance violations, such as data retention, exposing organizations to fines reaching up to 20 million dollars as imposed under GDPR. ROT also broadens the attack surface, which consequently increases the likelihood of data breaches that cost as much as 4.88 million dollars.

Lastly, ROT data is harmful for GenAI projects as well. LLMs are trained and fine-tuned on large volumes of data, and using bad data can not only affect the system’s efficacy but also result in poor responses.

DSPM solutions help organizations overcome all those challenges and risks through a policy-driven, automated approach. Instead of manual oversight, the solution creates a centralized inventory of all the organizational data. It then detects and flags obsolete data, categorizes data by sensitivity, and enforces tailored policies to either archive or remediate ROT data. DSPM identifies redundant data through an advanced cluster analysis technique. It helps pinpoint duplicate or near-duplicate data. This proactive approach to ROT minimization helps reduce costs and risks effectively.

An advanced DSPM solution leverages automated remediation. It integrates with federated systems like Slack, Jira, or ServiceNow to send quick alerts and updates. With federated automation, data teams can effectively maintain a lean and secure data environment, improve data quality, and enhance AI efficacy.