Exploring the Impact of Dark Data

Explore the concept of dark data, its importance, risks, and financial impact. Learn how to mitigate these risks and unlock potential insights from unused data.

What is Dark Data?

Dark data refers to unused, unstructured data that organizations collect, process, and store during regular business activities but do not utilize for other purposes. This data can include past employee records, financial information, transaction logs, confidential survey data, emails, internal presentations, download attachments, and surveillance video footage.

  • Employee Records: These are records of past employees which may include their personal information, work history, performance reviews, etc. They are often stored for legal reasons but are not used in day-to-day operations.
  • Financial Information: This includes transaction logs and other financial data that is collected and stored but not used for decision-making or other purposes.
  • Confidential Survey Data: This is data collected from surveys, which may include sensitive information. It is stored but often not used for further analysis or decision-making.

Why is Dark Data Important?

Dark data can provide valuable insights into internal processes and customer correspondences. It can help organizations determine which department owns what data, improve quality assurance processes, detect and correct process errors, look for privacy loopholes, and identify security vulnerabilities. However, it can also be a significant expense, with some estimates suggesting that dark data can cost a company up to $26 million annually in storage expenses.

  • Data Ownership: Understanding who owns what data can help in data governance and management.
  • Quality Assurance: Dark data can be used to improve quality assurance processes by providing additional information and insights.
  • Security Vulnerabilities: Dark data can help identify potential security vulnerabilities, helping organizations to improve their security posture.

What are the Risks of Dark Data?

Dark data poses several risks, including potential breaches of private customer records resulting in identity theft, and breaches of a company's sensitive information, for example relating to research and development. The risk of data leaks and thefts is particularly high with dark data due to its unstructured and often unsecured nature.

  • Identity Theft: Breaches of private customer records could result in identity theft, causing significant harm to customers and reputational damage to the company.
  • Sensitive Information Breaches: Breaches of a company's sensitive information, such as research and development data, can result in significant financial and competitive losses.

How to Mitigate the Risks of Dark Data?

Organizations can mitigate the risks of dark data by assessing and auditing whether the data is useful to the organization, employing strong encryption and security, and disposing of the data in a way that it becomes unretrievable.

  • Data Assessment: Regular audits can help determine the usefulness of the data and whether it should be retained or disposed of.
  • Encryption and Security: Implementing strong encryption and security measures can help protect dark data from breaches and thefts.
  • Data Disposal: Proper data disposal methods can ensure that the data becomes unretrievable, reducing the risk of it falling into the wrong hands.

What is the Financial Impact of Dark Data?

According to recent research, approximately 50 percent of a company's data is dark, which can be a significant storage expense. Estimates suggest that dark data can cost a company up to $26 million annually in storage expenses.

  • Storage Costs: The cost of storing dark data can be significant, particularly for large organizations with vast amounts of data.
  • Operational Costs: In addition to storage costs, dark data can also result in increased operational costs due to the need for data management and security.
  • Opportunity Costs: The potential insights and value that could be derived from dark data represent an opportunity cost if the data is not properly utilized.

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