What is Shadow Data?

Shadow data refers to untracked or unmanaged data created, stored, or shared outside the visibility and control of an organization’s IT and security teams. This data can include files, documents, or sensitive information housed in unauthorized applications, personal devices, or external cloud services. Shadow data poses significant risks to organizations, including data breaches, regulatory non-compliance, and inefficiencies in data management.

How Shadow Data Emerges

Shadow data often originates from well-meaning employees trying to enhance productivity. For instance, using unsanctioned file-sharing services to collaborate on projects, storing documents on personal devices, or leveraging external cloud apps without IT approval. Over time, this data becomes disconnected from the organization's centralized data governance, making it difficult to secure, track, or delete.

The Risks of Shadow Data

According to IBM's Cost of a Data Breach Report 2024, 35% of breaches involve shadow data, highlighting the proliferation of data and the difficulty in tracking and safeguarding it. Shadow data exposes an organization to:

Data Breaches: Unmonitored data is more likely to be mishandled or exposed, increasing the risk of breaches.

Compliance Challenges: Shadow data often resides in locations that don’t meet regulatory requirements, making compliance audits more difficult.

Lack of Control: Without IT oversight, organizations lose visibility into where their sensitive data resides and who has access to it.

Shadow Data vs. Shadow IT

Although they are closely related, shadow IT and shadow data represent distinct challenges within the broader landscape of IT governance, each with its own unique risks and implications.

Shadow IT

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Shadow IT refers to the use of unauthorized tools, applications, or devices within an organization without the knowledge or approval of the IT department. Employees often adopt these unsanctioned technologies to streamline their workflows or enhance productivity, bypassing official channels for convenience. While this may solve immediate challenges for individuals, it creates a fragmented and unmonitored technology ecosystem, complicating oversight and increasing security vulnerabilities.

Shadow Data

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On the other hand, shadow data is the byproduct of unmanaged or untracked data created, stored, or shared outside of IT’s control. This can include files in unauthorized cloud apps, sensitive information on personal devices, or outdated datasets forgotten on legacy systems. Unlike shadow IT, which focuses on the tools and devices being used, shadow data is about the information itself—where it resides, how it’s accessed, and the risks it poses.

Key Differences

Shadow IT involves unauthorized technology usage, while shadow data is about untracked information.

Shadow IT is often the cause, often leading to shadow data as a byproduct when employees use unsanctioned tools to handle company data.

Shadow data can exist independently of shadow IT, such as when outdated files remain on forgotten servers or unmonitored storage systems.

Why Addressing Both Shadow Data and Shadow IT is Crucial

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Organizations cannot effectively manage one without addressing the other. Shadow IT creates the conditions for shadow data to proliferate, while shadow data amplifies the risks introduced by shadow IT. Together, they represent a complex, interconnected challenge that requires a holistic approach to IT governance and data security. Ignoring either is akin to treating the symptoms without addressing the underlying cause.

How Shadow IT Contributes to Shadow Data

Shadow IT plays a significant role in expanding shadow data. When employees use unsanctioned tools, they inadvertently generate data that falls outside the organization’s visibility and control. For example:

Disconnected Data Storage: Files saved in unauthorized SaaS applications or external devices become inaccessible to IT teams.

Untracked Access: Shadow IT tools may lack enterprise-grade security controls, making it easier for sensitive data to be accessed or shared inappropriately.

Data Fragmentation: The proliferation of shadow IT leads to data silos, where critical information is stored in isolated systems, complicating efforts to enforce data governance and security.

While shadow IT focuses on the tools and services used without IT approval, shadow data emphasizes the unmanaged data created and stored in these environments. Together, they represent interconnected risks that require a holistic approach to mitigate.

Managing Shadow Data

Organizations can address shadow data by implementing comprehensive data governance strategies, including:

Data Discovery Tools: Deploy solutions that can identify and monitor SaaS usage across an organization, including unauthorized applications and cloud services.

User Education: Train employees on the importance of using approved SaaS tools and following data security policies.

Shadow IT Management: Proactively manage shadow IT to reduce the creation of shadow data and ensure all business-critical data is stored securely.

By tackling the root causes of shadow data—such as shadow IT—and enforcing strong data governance policies, organizations can reduce the risks and regain control over their data assets.

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