Introducing Column-Level Security for Your Data

‍

Data leaders face a critical challenge: harnessing the immense power of business intelligence without compromising on data security. The volume and sensitivity of data any company handles are not just assets but also liabilities if not properly secured. The key lies in smartly controlling who has access to what data and how this access impacts your business insights.

This is where the concept of tailored data access is pivotal. Data leaders need a system that doesn't just lock down data, but smartly partitions data–allowing the right stakeholders to tap into the right information at the right time, while maintaining compliance with complex regulations. With this method, data facilitates innovation and growth without it becoming a gateway for breaches or compliance nightmares.

This is why Column-Level Security (CLS) is not just a feature, but  a strategic approach to business intelligence—and is the reason Sigma is introducing CLS to all of its customers.

It's about ensuring that sensitive columns of data are accessible only to those with the need and the clearance, turning your company's data into a secure yet potent resource for decision-making and strategic advantage.

What is Column-Level Security?

CLS is a flexible and secure data access mechanism that gives organizations enhanced control over sensitive information. It offers granular control over the individual columns of data, giving organizations confidence that their sensitive data is protected and compliant with industry regulations. In Sigma, it is both easy to implement and easy to maintain.

The Advantages of Column-Level Security

Column-level security is another step in proactive risk management and data governance, providing four key benefits:

Protect Sensitive Information

Hide columns that contain sensitive information, such as personal identifiers (e.g., social security numbers), financial data, or medical records, to prevent data from falling into unauthorized hands. 

Data Sharing and Collaboration

Specific columns of data can be shared with external partners without exposing the entire dataset, fostering better collaboration to analyze data, share insights, and make predictions in a controlled environment. 

Data Confidentiality in Multi-Tenant Environments

To uphold strict data privacy regulations in multi-tenant or cloud-based environments, CLS ensures that each organization's data remains isolated from others and only the data about your organization is accessible.

Data Masking and Anonymization

When combined with modification or anonymization techniques, CLS protects sensitive data while providing a functional alternative where users can still gain the necessary data-driven insights. 

How Teams Enforce Column-Level Security

From finance to e-commerce, organizations across every industry leverage column-level security to protect sensitive information, provide confidentiality, and ensure regulatory compliance.

CLS for Healthcare

In healthcare, column-level security is often used to comply with HIPAA laws by hiding sensitive personally identifiable information (PII). For example, a managed care organization (MCO) is looking to reduce healthcare costs for states while improving the quality of care for beneficiaries. The department head supporting this company initiative must analyze high-level patient data to discover trends and outliers. Patient names and social security numbers are not needed for this particular analysis, so they are hidden from view, ensuring compliance with HIPAA.

CLS for Human Resources

An HR department at a tech company commonly uses CLS to govern its employee data.  A popular dataset might contain dozens of columns containing sensitive data, including address, phone number,  performance review scores, or salary information. Each of those columns has its visibility requirements; payroll can see some, managers can see a few, and tax professionals can see others. With CLS, the HR team can easily manage employee data and ensure only the correct individuals have access to the right information.

CLS for Embedded Analytics

For a company implementing CLS with their embedded analytics platform—where analytics are provided externally to customers in an application—hundreds of customers may view the same dataset with unique combinations around which roles can see each column. Administering and maintaining that list for thousands of individual users across hundreds of organizations would be nearly impossible and increasingly expensive. 

In Sigma, by pairing CLS with teams and user attributes, they can distribute the workload by setting up a single user attribute that controls the CLS for each sensitive column. From there, each customer can assign teams or individuals to the right level of visibility. No duplicating datasets, reports, or maintaining the column-level security mapping across thousands of users. Column-level security takes embedding sensitive data from an unmanageable and unscalable process and makes it simple yet secure. 

Conclusion

Column-level security ensures that data remains accessible and reliable to the right individuals or teams so they have the insights they need to make data-driven decisions while safeguarding against unauthorized access. In Sigma, column-level security is coupled with teams and user attributes for flexibility in permissions, allowing organizations to provide a better experience to their internal and external customers while adhering to strict security and compliance protocols. 

‍

Learn more about column-level security, and see Sigma in action here.

‍