What is DCAP (Data-Centric Audit and Protection)? A Definition of DCAP, How It Works, Best Practices, and More
Enterprises are taking advantage of big data analytics to advance their businesses. With big data arriving, there is also more opportunity for cybercriminals. That’s why companies are increasingly securing their business and customer data with data-centric audit and protection (DCAP).
A Definition of Data-Centric Audit and Production
Data-centric audit and protection (DCAP) is a term used by Gartner, a business research and consulting company, to describe a type of data-centric security. The goal of DCAP is to protect an organization’s data privacy and apply it to specific pieces of data, not the entire organization.
DCAP focuses on:
- Classifying data
- Storing sensitive data
- Data security governance
- Protecting data against unauthorized access
- Data monitoring and auditing
How Data-Centric Audit and Protection Works
Data-centric audit and protection is about protecting the data, not about preventing unauthorized users from hacking into systems. This layer of protection relies on several steps to secure data:
Best Practices of Data-Centric Audit and Protection
Data-centric security is a holistic strategy. It doesn’t discriminate against device, storage technology or platform. Ensure complete data-centric audit and protection with best practices such as:
Secure infrastructure
Reporting and auditing
Encryption key management
Data discovery
Search and destroy
Content discovery technology can help discover data hiding where it should be. Business organizations need to find it before unauthorized users do.
Data-centric audit and protection is vital for modern enterprises that leverage big data to support business processes. By finding the right balance between adequately protecting your organization’s data and supporting the use of data within the organization, you’ll create a more robust security posture without hindering productivity or sacrificing the benefits of big data.