I've been living in Vision One for a few months now, mainly for the detection and response side, but I kept feeling like I was underutilizing the data it collects. The out-of-the-box dashboards are great for high-level SOC stuff, but I wanted to slice it for product-related insights—like which detection rules fire most for our specific user cohorts, or tracking mean time to acknowledge across teams.
So, I dug into their Workbench query export. The pivot to Power BI wasn't as straightforward as I hoped; the raw JSON needed some massaging to relate entities like alerts to their associated hosts/users properly. I ended up creating a data model that treats the Workbench search results as a fact table, with separate dimension tables for host, user, and detection rule.
The real win was building a few product-analytics focused reports:
* **Feature Flag Correlation:** Overlaying our launchdarkly flag events (imported separately) with security alert timelines. Sounds niche, but we actually spotted a correlation between a new backend feature flag and a spike in "suspicious process" alerts from a specific service. Turned out it was a benign scripting change, but it was caught before it escalated.
* **User Journey Risk Scoring:** This is experimental, but I'm trying to map high-risk security events (like repeated blocked executions) to user segments (e.g., "new users in first week"). It's helping us tailor security training prompts in the app itself.
Has anyone else tried pulling Vision One data into an external BI tool? I'm curious if you ran into similar schema challenges or found other interesting joins. The "MITRE ATT&CK techniques" dimension feels like it has potential for trend analysis over time, but I haven't built that out yet.