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6 Dark Data Risks

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Dark data is data that an organization collects but doesn't use. It is common for organizations to have more dark data than regular data. The primary drivers of this are inexpensive data storage and sensors. Secondary factors are high volumes of data related to social media, communications and automation. Businesses tend to have an optimistic sense that data has value, even if they have no immediate plans to use it. Data is often viewed as no-risk, no-cost but potential future reward. This view is increasingly called into question as firms incur losses related to information security and compliance. Holding dark data has several risks:

Reputational Damage

Any data you store might be leaked by an information security attack. As it is your responsibility to protect such data, this represents potential liability, compliance costs and reputational damage.

Loss of Proprietary Knowledge

When data isn't used there is a tendency for people to forget its content, purpose or even its existence. There is a further tendency for such data to go unmanaged and be more vulnerable to security risks such as unauthorized access that may leak trade secrets and other proprietary knowledge.

Future Compliance

The cost of compliance to future data related laws, regulations, rules and governance standards. Such requirements can be significant challenges when an organization has collected a large number of mysterious data repositories.

Legacy Costs

In many cases, data loses most of its potential value in less than a year but remains for decades consuming resources. Cleaning up this data can be a significant cost and its presence and be a drag on operational efficiency.


Collecting copious amounts of dark data can actually get in the way of efforts to leverage data for business purposes. Dark data is essentially a type of anti-information that serves no purpose but makes it more difficult to find valuable information. Imagine the task of conducting a data asset inventory in the context of thousands of aging and poorly documented dark data repositories.


At the macro level, dark data consumes significant data center capacity on a global basis and represents a wasteful practice.
Overview: Dark Data
Data that an organization has collected but hasn't used.
Related Concepts


This is the complete list of articles we have written about data.
Abstract Data
Atomic Data
Big Data
Cohort Analysis
Dark Data
Data Analysis
Data Architecture
Data Attribute
Data Cleansing
Data Collection
Data Complexity
Data Consumer
Data Control
Data Corruption
Data Custodian
Data Degradation
Data Dredging
Data Entity
Data Federation
Data Integration
Data Integrity
Data Liberation
Data Lineage
Data Literacy
Data Loss
Data Management
Data Massage
Data Migration
Data Mining
Data Owner
Data Producer
Data Quality
Data Remanence
Data Risks
Data Rot
Data Science
Data Security
Data States
Data Transformation
Data Uncertainty
Data Veracity
Data View
Data Virtualization
Data Volume
Data Wipe
Decision Support
Deep Magic
Empirical Evidence
Event Data
Hard Data
Information Assurance
Legacy Data
Machine Data
Market Research
Master Data
Misuse of Statistics
Personal Data
Personal Information
Predictive Analytics
Primary Data
Primary Research
Qualitative Data
Qualitative Info
Quantitative Data
Raw Data
Reference Data
Small Data
Soft Data
Source Data
Statistical Analysis
Statistical Population
Structured Data
Transaction Processing
Transactional Data
Types Of Data
Unstructured Data
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