Data classification and inventorying: The foundation of regulatory compliance

Data classification and inventorying: The foundation of regulatory compliance

Data classification and inventorying: The foundation of regulatory compliance

Succeeding as a business means capitalizing on data, and managing that information effectively means complying with regulations. These guidelines and laws vary, but some practices lay crucial groundwork for virtually all of them. Data classification and inventorying are two of these foundational steps.

Data classification is the process of separating an organization’s information into defined categories. Inventorying, also called mapping, then tags and compiles this data, including their relationships and movements, into a single source of truth. Both practices have many benefits apart from regulations, but they’re an increasingly important part of compliance.

A tightening regulatory market

Data classification and inventorying has become even more central to doing business as data regulations grow in number and strictness. Companies must meet far more stringent data management standards, and it’s harder to do so without having a foundational understanding of the amount and type of sensitive data sitting on their business systems. 

For example, the GDPR requires data processing agreements (DPAs) in certain business relationships. These DPAs must cover many specific details, including the type of information being collected. Having a data inventory ready to go enables companies to write, sign and implement a DPA far faster and makes compliance less disruptive and time consuming.

Data Classification and Inventorying in Regulations

Some of the most prevalent regulations today outright require data classification and inventorying. The GDPR requires records of processing activities from data controllers and processors. While the verbiage uses alternate language, the records they request are, ultimately, sensitive data inventories. 

Under this part of the GDPR, organizations’ records must include data categories, subject groups, why they process this information and who receives it. Businesses must also make these inventories available to authorities upon request. That requires extensive classification and inventorying practices, and failure to meet these requirements carries hefty fines.

Other regulations, like the California Consumer Privacy Act (CCPA), don’t specifically call for classification and inventories but functionally require them. The CCPA gives California residents the right to know what data businesses collect on them and how they share and use it. Providing that information upon request necessitates a readily available data inventory.

How Classification and Inventorying Impact Compliance

Even when applicable regulations don’t require data classification and inventorying, these practices serve a crucial role in compliance. Here are a few reasons why these steps are so foundational to meeting current regulatory requirements.

  1. Knowing exactly what data is on your business systems is a critical starting point

One of the most important roles of classification in driving compliance is providing business with a critical starting point via visibility across all critical business systems. In order to protect sensitive data, the organization needs access to simple, easy to understand reports detailing what kinds of data are in their possession, how much of each type they have, to which regulation it correlates, and who has access to it. 

Prior to putting their name and reputation on the line with regulatory bodies, most companies will perform internal audits. They do this to ensure they’re fully aware of everything in their possession, which includes becoming aware of “dark data.” Dark data refers to data that’s being stored in various locations and has not yet been classified, labeled or accounted for, and is therefore unknown to the organization. Having a system in place that finds, labels and brings visibility to unknown data in all locations enables a more comprehensive data protection strategy. It also protects the company from data theft and breaches, which are part of regulatory expectations and when not properly secured, can lead to fines. For instance, credit card holder data that is retained after a transaction is a breach of PCI and data protection regulations. Unknown data can not be deleted to meet right to be forgotten requirements.

  1. Because if you don’t know what you have, you can’t protect it

Having a sensitive data inventory in-hand provides another critical advantage for meeting a universal regulatory requirement: putting proactive security measures in place. Data classification and inventorying can reveal where private customer information is sitting and who has access to it, making visible which controls need to be put in place to protect it. Considering how many regulations require evidence of steps taken to secure data, that insight is crucial.

Once data is uncovered and classified, it reveals any critical gaps in controls that need to be put in place to protect it. This process also reveals if an organization’s collection or storage processes create critical exposure points. For example, is customer PII in a publicly accessible folder? Is private data being accumulated by employees, unknowingly or unintentionally? Data may need to be cleaned, organized, or migrated data, but first, it must be identified. 

Many regulations also require companies to notify users after a breach within a certain time frame. Meeting that timeline is far easier when the company can pinpoint the origin of the problem and view a complete record of how sensitive data moved across employees.

  1. Easier, faster compliance with new regulations

Data classification and inventorying also make it easier to adapt to regulatory changes. When it comes to the relatively young field of data privacy, the regulatory landscape is continually evolving, requiring frequent adaptation.

Security certifications now optional in the EU may become mandatory by 2023 under the EU Cybersecurity Act. Similarly, many states are suggesting and passing new regulations inspired by the GDPR and California’s CCPA. Organizations that hope to stay compliant in this changing environment must have full insight into their data and the processes that affect and use it.

Data classification provides the foundational information businesses need to determine how they can meet emerging regulations. Inventorying makes it easier to see if any once-permissible processes must change to enable ongoing compliance. Adjusting to meet new requirements without these measures could be time-consuming, challenging and costly.

Data Classification and Inventorying Best Practices

Given this rising importance, businesses should familiarize themselves with some best practices surrounding classification and mapping. Here are a few to keep in mind.

Companies may find themselves under the jurisdiction of several different regulations. If that’s the case, their classification approaches should align with the most stringent or specific standards. That will be the easiest way to satisfy all codes the business may fall under. Security teams should also work with all data stakeholders to reveal the best way to classify their information.

Remember that data classification can take considerable time if done manually, and classification mistakes could be costly under some regulations. Workers often spend more time finding and organizing information than analyzing it. 

Stay Compliant With Data Regulations with Qostodian Recon

Classification and inventorying alone aren’t sufficient for regulatory compliance and security. However, they’re a critical first step to meeting growing regulations. Recon automatically detects every sensitive data element on-premises or in the cloud, and automatically let’s you know the regulation to which it applies. Going forward, once legacy, unstructured data has been cataloged, Recon tells you exactly what new information has been added to your business systems, so that teams no longer have to spend time re-running scans for every compliance requirement. 

Leading financial institutions such as CAA and Kaleido chose Recon, which was designed from the CPU up to defy legacy scanning limitations, to drive compliance for the following reasons: 

  • Sensitive data remains anonymized and never leaves their environment 
  • Surgically precise results are delivered 60x faster than alternatives, across every location and file type, including on-premises locations, cloud drives, Workstations, OneDrive and more. 
  • In terms of providing evidence that adequate steps were taken to protect data, Recon ranks, quantifies and contextualizes risk to show information security teams exactly where to focus to have maximum impact. 
  • Tracking occurs at the data element level (rather than the file level, because files, or the container, change all the time). This enables:
    • Proactive notifications of data accumulation, exfiltration, deletion by employees
    • A historical record of data movement across employees to eliminate manual investigations and ensure notifications in a timely manner
  • Keyword search is included in the original cost, enabling users to see the origination point of a specific data leak and everyone the leak touched. Some customers also use it to ensure data isn’t on the dark web.
  • A single fee for usage, based on employee count, while offering comparable functionality to alternatives. The cost does not go up for each new environment scanned, amount of data being ingested, or when we add new functionality.

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