There are several concerns that organizations may have about sensitive data discovery. Some of the major concerns include accuracy, data p[rivacy, scalability, integration with existing systems, and cost.


One of the primary concerns with sensitive data discovery is the accuracy of the results. The tools used to identify data may not always be able to accurately distinguish between sensitive and non-sensitive data, leading to false positives and negatives. This can result in sensitive data being overlooked or non-sensitive data being flagged as sensitive.

Data Privacy

Sensitive data discovery involves scanning data stores and systems to identify sensitive information, which can raise privacy concerns. Organizations need to ensure that they are complying with data protection regulations and that sensitive data is being handled appropriately.


For large organizations with vast amounts of data, sensitive data discovery can be a time-consuming and resource-intensive process. organizations need to ensure that their sensitive data discovery process is scalability to accommodate growing amounts of data.

Integration with Existing Systems

Sensitive data discovery tools need to be integrated with existing systems, such as cloud-based storage and data management platforms. Ensuring that these tools work seamlessly with existing systems can be challenging and require additional resources.


The cost of implementing sensitive data discovery tools and processes can be significant, particularly for smaller organizations with limited resources, but will be a higher return on investment as it prevents the organization from getting fined.

Meet C² Discover

C² Discover is your sensitive data discovery tool. With C² Discover, easily connect to existing systems, find and identify sensitive data found in your data, understand what was found, and apply what was discovered to your data privacy initiatives to meet regulations.

C² Discover connects to your data environment and combs through your data for sensitive data using a collection of technology. Our data scientists combine machine learning and artificial intelligence to provide the user with thorough, but accurate results of what’s in the cloud. To avoid false positives and negatives, C² Discover combs through the data elements, ignoring the column, row, or table names.

Find what was found and where you’re most vulnerable through the interactive user interface. Get a visual and know the specifics of what was found in multiple views, from an overview to a granular view. Feed what you learned into your favorite data privacy tool or data privacy initiative to meet regulations like Gramm Leach Bliley, HIPAA, CCPA, GDPR, and PCI-DSS.

To address these concerns, organizations can implement best practices such as regularly testing and fine-tuning data discovery tools, ensuring that data protection regulations are being followed, using scalable and efficient tools, and carefully assessing the costs and benefits of implementing sensitive data discovery tools.