You're managing sensitive data in real-time BI reports. How do you guarantee its security?

When I decided to publish our report server to the internet, I bought a SSL certificate to ensure secure communications between clients and server. This SSL certificate is renewed each year with a new CSR to ensure its effectiveness.

Access control is the biggest factor in maintaining data security. Views and core data should be pre-filtered based on the login used to access. Depending on how sensitive the data is you may want to consider disabling options to download the data, or having it accessed only through a controlled RDP environment.

In addition to security control feature in Power BI RS, I use RLS to ensure each user can see only data which they are allowed to see, and nothing more. Users have almost the same access to the reports as they have on our operational platform.

We have put our server behind a set of firewalls which are constantly monitored and updated by our security team. We have also performed a completed security check and penetration test before publishing our report server on the internet. Firewalls also control access on our company's network, ensuring each user can do what they are allowed.

Prioritize the security of sensitive data in real-time BI reports by employing Secure APIs from the ground up. By designing APIs with built-in security, implementing zero-trust frameworks, continuously testing through automated strategies, and monitoring for threats in real-time, you ensure robust protection. Additionally, leverage generative AI and LLMs to stay ahead of evolving threats. My advice is to integrate these security practices early in your API development to build resilience and safeguard your data effectively

Employing data masking techniques is an effective way to protect sensitive information in real-time BI reports. Data masking involves replacing sensitive data with anonymized values, ensuring that the actual data is not exposed during analysis and reporting. This technique is particularly useful for testing and development environments where real data is not necessary. By using dynamic data masking, sensitive data can be masked in real-time, providing an additional layer of security. Regularly reviewing and updating masking rules ensures that they remain effective and aligned with security policies.

In addition to the primary strategies, it is important to implement regular security training for all team members to ensure they are aware of best practices and potential threats. Conducting periodic security audits and penetration testing helps in identifying and addressing vulnerabilities. Staying updated with the latest security trends and technologies ensures that the security measures remain effective against new threats. Collaborating with security experts and using automated security tools can enhance the overall security posture, ensuring comprehensive protection of sensitive data in real-time BI reports.