If the idea of comparing the current expansion rate of global data production with the rate of growth of the universe from the Big Bang seems a little hyperbolic, consider: nearly 90% of all the information in human existence has been created in just the last few years alone. In fact, as of 2020, every person on the planet produced nearly 1.7MB of data every second — an unprecedented and nearly unimaginable figure.
Naturally, managing that data has become increasingly more challenging as data velocity and volume have increased. That’s especially the case when considering how and by whom that data can be accessed or used, governed both by company policy and, more importantly, by industry and government regulations.
Effective and thorough data classification is a core component to consistently meeting and exceeding data management regulatory standards. Failing to meet those standards — high-profile and expansive regulations like the GDPR, HIPAA, PCI, and others — can result in punitive fines and fees, legal liability, and irreversible damage to consumers’ trust in a brand.
Yet, despite these obvious and significant risks, many organizations still struggle to effectively catalog every byte of data in their environment because today’s enterprise data lives in many platforms, applications, devices, and machines that reside beyond the reach of legacy data classification tools with limited capabilities and a heavy reliance on manual data management operations.
The problem with manual data classification
Every social security number, medical record, customer file, or other piece of sensitive information has a level of sensitivity and confidentiality that defines the level of protection it commands, including who can view it and how it can be used. But legacy tools and methodologies tend to leave huge gaps in data privacy management because the data sets are too large to manage manually and because data is constantly evolving — new data is added, and existing data is being moved, copied, or altered — that increases the degree of difficulty in maintaining appropriate classifications.
What’s more, even if manual classification could keep up with the volume of data and the velocity of its evolution, human subjectivity lends itself to misclassifying a piece of data — what may seem extremely sensitive to one user might not to another. This type of oversight is considered negligent, but intentional misclassification can, and does, occur as well in an effort to curb operational inefficiencies. When users must be continuously authorized and validated in order to access sensitive data for day-to-day use, as is the case in Zero Trust environments, it naturally tends to slow things down. To avoid this, highly sensitive data ends up being classified with the lowest level of security measures, leaving it exposed to risk.
To regulatory agencies, the universal understanding that humans aren’t perfect isn’t a reasonable excuse for noncompliance. When it comes to securing sensitive data, there’s no room for mistakes, especially when technology exists that ensures accuracy, like automated classification. This machine approach removes the danger of an insider attack — negligent or intentional — because classification levels cannot be changed and the data itself is labeled with standardized naming conventions. This enables it to be easily understood by others on your team and appropriately processed by other platforms in your security stack.
Data classification for automated regulatory compliance
Modern data lifecycle management requires modern solutions, and both IT and business leaders are increasingly seeking automated and more robust data classification solutions to help keep their data safe and their businesses out of legal trouble.
Luckily, this new generation of data classification solutions can automatically (and persistently) classify data, updating its tags as it moves through the data lifecycle. Now, any time data changes in any manner, for any reason, it’s classified with the appropriate tags for access, use, and archiving. Ultimately, an automated classification tool simplifies an increasingly complex, but vital, data security operation by:
- Unburdening IT teams of time-consuming manual work.
- Significantly enhancing a company’s ability to comply with ever-changing compliance requirements.
- Improving risk-related decision-making and responses with real-time data.
In the event of a data breach, having compliant security measures in place based on accurate classification can even help to reduce the fines imposed by regulatory agencies.
Automated, compliance-ready data classification with Spirion
Spirion delivers unrivaled persistent data classification capabilities to help organizations of all sizes, in any industry, properly protect their most sensitive information and easily keep pace with changes and updates to even the most stringent data governance compliance regulations.
Spirion helps organizations assert greater control over their enterprise data, no matter where it resides in their IT environment. Unlike tools that rely on catalog-based classification that scans for metadata or column names for label assignment, Spirion provides a more robust, responsive, and scalable classification solution that:
- Classifies each piece of information with purpose. This includes dynamic classification labeling, which updates classification labels when labels are modified or added.
- Categorizes and tags data automatically based on sensitivity and existing information security policy and processes, regardless of how many times data is moved or copied.
- Features at-a-glance, user friendly icons and classification markers for each bit of data.
- Automatically labels data based on its purpose of collection, the process through which it was collected, and its privacy level, then federates labels across the entire IT environment
Spirion solutions streamline and simplify data classification activities across every type of data, in every location across the IT environment, helping enterprises across industries and markets quickly, reliably, and continuously update data classification from a single platform to dramatically enhance their data compliance initiatives while also protecting their bottom line.