Dark data continues to be a major challenge in enterprises, and its time that the security risks that are associated with are identified and mitigated.
Multi-cloud frameworks have become increasingly popular in recent years. Many organizations have been working in highly distributed and remote environments during the COVID pandemic.
Organizations are now creating, storing, and managing massive volumes of data across various cloud platforms. Despite the extent of this trend, businesses typically have little or no visibility into much of the data that resides in these clouds. This has accelerated the rise of dark data.
Identifying and analyzing all data is extremely challenging when enterprises construct multi-cloud frameworks and slide data across numerous containers and components. Dark data, unsurprisingly, poses substantial security and compliance risks. There is no simple way to determine which data systems are in use, what data is stored in cloud components, and how this data is protected.
Hence, businesses must move beyond basic inventory tools that only deliver a limited insights into cloud data. It’s crucial to adopt a more sophisticated approach that provides comprehensive visibility into your organization’s asset footprint and allows you to take specific steps to minimize risks.
Critical Challenges
According to a recent study, dark data is extremely concerning to 84 percent of organizations. This is the data that organizations aren’t aware of, but which accounts for more than half of all data in existence and can be extremely sensitive or critical.
Unstructured data is the most difficult to manage and secure for eight out of ten organizations. Unstructured data generally comprises a variety of sensitive information and is difficult to scan and classify due to its inherent complexity.
More than 90 percent of businesses have trouble enforcing security policies involving sensitive or critical data. Sufficient data policy reach and enforcement are crucial for proper management, remediation, protection of data assets.
Managing Dark Data
Data governance, security, and privacy best practices all revolve around the ability to discover dark data and manage it more efficiently. The access management and data storage frameworks in an enterprise can also be improved with the correct foundation in place.
The following are some of the critical steps for breaking down data silos and stamping out dark data:
Discover: All shadow and native data assets that reside across major cloud service providers must be identified, and once they are detected, organizations must extract them into an asset catalog.
Detect Risks: Organizations must also identify any security and compliance risks associated with dark data assets and remediate exposures.
Secure Systems and Govern Access: An organization can now build a relationship map between the discovered personal data and its owners. An enterprise can fully understand its security risks and govern access at a granular level with this visibility.
Fulfill Privacy Obligations: With personal data mapping in place, an enterprise can execute timely and accurate fulfillment of Data Subject Requests (DSRs), breach notifications, and consent management.
Concluding Words
Data is an organization’s most valuable asset, relying on it every day to make critical strategic and operational decisions. Unfortunately, most of this data is highly sensitive or critical, and it can be exposed accidentally or maliciously in some instances.
Sensitive or critical data is being proliferated throughout the environment at unprecedented rates due to the rapid growth of public, private, hybrid, and multi-cloud models. As the scope of this type of data expands, so does the risk to the organization.