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Shadow data is data that an organization possesses but is not actively tracked, managed, or officially recognized by its data governance processes. This can include duplicate files, old backups, or data stored in unauthorized locations like personal devices or cloud services. Because it’s not centrally controlled, shadow data can pose significant security risks, such as data breaches or compliance violations, since it may fall outside regular protection and monitoring systems.
The proliferation of shadow data is often driven by the use of shadow IT, where employees, bypassing corporate IT policies, leverage personal applications or consumer-grade cloud services to store and share sensitive information. These practices can undermine an organization’s data protection protocols, leaving critical information exposed to security vulnerabilities.
The existence of shadow data introduces numerous security and compliance challenges for organization, including:
Unauthorized access, storage, or sharing of shadow data can lead to breaches of sensitive or proprietary information, potentially exposing your organization to cyberattacks or data theft.
Shadow data is often stored in unauthorized environments that do not comply with regulatory requirements, such as GDPR, HIPAA, or CCPA. This exposes organizations to potential fines and reputational damage.
Data stored outside of the purview of IT departments can be difficult to track and manage, creating gaps in security protocols and potentially leading to unauthorized access or data loss.
Identify Shadow Data to Mitigate Security Risks
Implement a Strong Governance Strategy
Prevent Shadow Data from Accumulating
Q: What is the difference between shadow data and dark data?
A: Shadow data refers to unmonitored, unmanaged, or forgotten copies of sensitive data that exist outside official security and compliance measures, such as backups, temporary files, or cloud storage left behind by employees.
Dark data, on the other hand, is data that organizations collect but do not use, process, or analyze – such as log files, old customer records, and unstructured data stored in archives. While both pose security risks, shadow data is particularly dangerous because it often contains sensitive or regulated information outside an organization’s visibility.
Q: How does shadow data get created?
A: Shadow data is unintentionally created in various ways, including:
Q: What are common examples of shadow data?
A: Shadow data can take many forms, such as:
Q: Does shadow data affect regulatory compliance (e.g., GDPR, HIPAA, CCPA, etc.)?
A: Yes, shadow data can lead to compliance violations because organizations are responsible for protecting all sensitive data, whether they actively use it or not. Key compliance risks include:
