In today’s data-driven landscape, unstructured data risks are mounting. With 90% of data being unstructured – practically doubling each year – and spread across multiple repositories, managing and maintaining its quality and security has become progressively challenging, impeding transformation and creating business risk. A strategy to effectively manage this data is no longer “nice to have” – it’s essential.
The Risks of Improperly Managed Unstructured Data
At its core, data risk is business risk. If organizations cannot access or analyze their unstructured data—ranging from emails and documents to videos and images—they become susceptible to various risks including sensitive data exposure, compliance violations, and wasted technology investments.
Improperly secured sensitive data
If this data is stolen, corrupted, or encrypted it can cause significant financial damage including: business downtime, regulatory fines, loss of reputation/revenue, and costs to repair breach.
Data exposed by employees, whether intentionally, unintentionally, or through GenAI outputs
A significant threat to data risk comes not only from malicious actors but from internal users. Although they may not intend to cause harm by sharing a payroll list with a third party, for example, the result could be a privacy violation that can lead to reputational damage, financial loss, and regulatory fines. Exposure of sensitive data, whether through employee actions or outputs generated by generative AI, poses a serious risk to the organization.
Inability to locate personally identifiable information (PII) across systems
Locating data on an individual to comply with regulations like the California Consumer Privacy Act (CCPA) can be a significant drain on resources. Lack of visibility into where or how this data is stored also raises the risk of fines for non-compliance. Even unintentional violations could cost organizations $2,500 per infraction.
Having too much stale or duplicate data
There are several risks when it comes to stale data. First, with the explosion of data production, storage costs are increasing both on-premises and in the cloud. Second is the category of data breach and regulatory non-compliance. Just because you aren’t using the data, doesn’t mean it can’t hurt your business if it is exposed—particularly if it’s sensitive. And finally, duplicate and stale data can lead to noise, biases, and hallucinations in AI training, compromising the relevance and accuracy of GenAI outputs.
Failure to present a clear and comprehensive overview of data protection to auditors
The number of active data security and privacy regulations is growing rapidly and enterprises need to ensure auditors that they’re taking steps to maintain compliance. Failure to do so can lead to more significant fines. Since it went into effect in 2018, the GDPR has assessed more than 2,000 fines, worth more more than $4.9 billion cumulatively.
Overcome the Unstructured Data Challenge
By making complex unstructured data accessible, analyzable, and actionable at scale, organizations can mitigate risk and ensure their enterprise data is always ready to support a variety of mission-critical business initiatives.
Download our latest whitepaper to learn how, with intelligent data management, you can turn the unstructured data challenge into an opportunity, unlocking the full potential of your data to drive sustainable growth and innovation.
