Authored by Michael Orozco, Managing Director, Cybersecurity Services

In today’s world, data is king, and protecting that data is paramount for any enterprise. But as the volume of unstructured data continues to grow exponentially, traditional data loss prevention (DLP) methods are becoming less effective. In this article, we explore the challenges that unstructured data presents to modern enterprises and examine new approaches that can help keep sensitive information secure. Discover how encrypting sensitive data using advanced algorithms can protect your enterprise from data loss, safeguard your data, and ensure compliance with regulatory frameworks.

Protection and Compliance for Unstructured Data in the Modern Enterprise

Data Loss Protection (DLP) efforts have historically been founded on a broad spectrum of tools and processes used to secure sensitive data from being exfiltrated, misused, or accessed by unauthorized users. DLP software helps enterprises to classify regulated, confidential and business critical data.  It also helps to identify violations of policies defined by the enterprise or within a predefined policy framework.  In some cases, the policies are driven by regulatory compliance such as HIPAA, PCI-DSS, or GDPR. Often the policies are driven by trade secret, sensitive intellectual property, national security information classified as Secret, or are required to be protected by court orders or legal actions.

Currently in popular use is the time proven method of blacking out words, sentences, or paragraphs that need to be redacted.  This can certainly be considered ‘old school’ DLP, but it does work to some extent.

What if it were possible to highlight the words, sentences, or paragraphs intended to be protected to then encrypt them with complex algorithms? This could all be done at the source copy of the document and with permissions set such that the same document is redacted by encryption differently for each user depending on the user’s defined roles, permissions, and policies.

State of Data in the Modern Enterprise

Recent reports indicate[1] that up to 80% of data in the enterprise is in unstructured form such as PDF, Microsoft Office documents, emails, and messages in enterprise messaging apps, etc. In regulated industries especially, unstructured data poses a significant challenge to those charged with preventing the leakage or loss of such data. Compounding the problem is the fact that the amount of unstructured data is doubling every two years[2]. Unstructured data is a concerning source of leaks and data loss, for example, 47% of financial services employees say they have downloaded, saved, or sent work-related documents to their personal accounts before leaving or after being dismissed from a job[3]. These figures do not account for the number of DLP incidents where data is viewed inadvertently by unauthorized users and later shared.  This problem is expected to become more pressing, especially as enterprises transform to be more distributed in both infrastructure (90% of enterprises use multi-cloud[4]) and operation (with hybrid-office work becoming the norm after the pandemic).  Regardless of the technological advances, the premise never changes.  It’s about the unauthorized viewing or sensitive data that can’t be unseen or stopped from being shared.


As unstructured data continues to grow and present new challenges for enterprises, it is clear that traditional DLP methods are becoming less effective. However, there are new approaches, such as encrypting sensitive data using advanced algorithms, that can help keep sensitive information secure and ensure compliance with regulatory frameworks. In our second article, we will discuss the challenges of protecting unstructured data and the requirements for adoption of an effective protection solution. We will also explore the benefits of proactively and effectively protecting unstructured data as it travels and lives inside and outside the enterprise and provide some guidance on what to look for when evaluating potential solutions.


[2] Investing in the Explosive Growth of Unstructured Data – Nanalyze

[3] Insider Threat Statistics You Should Know: Updated 2022 – Tessian