Overall, ThreatConnect Risk Quantifier is powerful, but there are some areas for improvement. A few areas could be better; first, the learning curve is steep for new users, and a guided onboarding or tutorial would help. Second, report customization could be more flexible so different teams can see exactly what they need. Additionally, handling very large data sets can slow down occasionally, so performance optimization would be helpful. Finally, adding more predictive analytics or AI-driven insights could automatically highlight unusual risks or trends without manual analysis. We mostly work on data, so we face many challenges with large data sets when using ThreatConnect Risk Quantifier. When you feed very large data sets into RQ, such as hundreds of applications and thousands of vulnerabilities, the performance can sometimes slow down during scoring or dashboard updates. It doesn't break, but processing can take longer than expected. This is mostly unnoticeable during bulk imports or complex scenario analysis, so planning updates during off-peak hours or breaking data into smaller batches can help. Overall, it's reliable, but performance could be improved for very large-scale data and environments. It would be great to have more interactive dashboards that let users drill down easily without leaving the main view. Another useful addition could be automated alerts or notifications when risk scores change significantly, so the team doesn't have to check a dashboard constantly. Lastly, more built-in guidance or AI tips for interpreting FAIR-based metrics could help new users to get up to speed faster. Overall, the tool is strong, but these additions would make it even more efficient and user-friendly.
