When organizations consider data protection, they often focus on the security aspects of the systems around the data - encryption, access control and compliance requirements.
While important, these elements should be secondary to a clear view of where sensitive data – especially personally identifiable information (PII) – resides across company systems.
However, obtaining this visibility – through data discovery – can be the hardest part of the data protection puzzle.
You can’t protect what you can’t see
In today’s digital landscape, most organizations use a combination of on-premises, cloud and SaaS services. They store vast quantities of data in fragmented systems with decentralized control.
Sensitive data can be found in the places it’s expected to be, such as in databases, CRMs, data lakes and warehouses. But huge volumes of personal information can be found elsewhere as well, including email, collaboration tools, file shares, logs, storage backups and more.
This, along with the added complexity of shadow IT and dark data, makes data discovery an almost impossible task to accomplish without purpose-built solutions.
The complexity of data discovery
Data sprawl across fragmented environments
Businesses today operate highly distributed networks, increasingly turning to cloud-first environments for maximum flexibility and scalability without the maintenance demands of the underlying infrastructure. Multi-cloud strategies are becoming the norm, to avoid vendor lock-in and provide resilience. In addition, SaaS adoption rates continue to grow, further expanding an organization’s data sprawl.
Exponential data growth
We’ve experienced unprecedented data growth over the last decade, especially in unstructured data, which now accounts for around 90% of all data within an enterprise estate (IDC).
Unstructured data is a vast resource that many businesses struggle to utilize effectively, its secrets remaining hidden and untapped. It can also be a data security risk, containing significant quantities of sensitive information without the oversight and control to ensure its security.
The challenge of unstructured data is only set to increase, as the rapid advancements and adoption of AI across business applications drives dynamic data creation and transformation with each new query.
Decentralized data security and risk management
The highly disparate nature of organizations’ digital landscape means that data ownership is decentralized, with limited (if any) visibility across the whole environment. Alongside accelerating rates of data creation and transformation, the risk exposure of organizations without adequate data management capabilities is likely to rise dramatically.
As a result, there’s great pressure on organizations to comply with evermore stringent legal and regulatory demands for data protection and privacy compliance. Common across these requirements is the establishment of a centralized data inventory, cataloging data across the organization, as a first step toward effective risk assessment, governance and control.
Make data discovery easy with Ground Labs
Ground Labs products enable organizations to uncover hidden stores of personal data and gain visibility across their digital estate, on-premises or in the cloud.
Unlike many solutions on the market, derived from a system-led view of data protection, Ground Labs’ tools deliver a data-first approach built on our award-winning GLASS discovery engine. With over 300 pre-configured PII data types from more than 50 countries, Ground Labs data discovery tools deliver fast and accurate data discovery and remediation capabilities designed for data protection and privacy compliance.
To find out how Ground Labs can help your data protection strategy, request a demo or book a call with one of our experts today.