Skip to main content

Evidence Model Plan

EventLinx uses operational and system data to support reliability, security monitoring, and internal decision-making. This includes signals from production systems, application logs, and analytics outputs that help teams understand system health and usage trends.

The documentation website only describes these practices at a high level. The actual processing and storage of data occurs in production and analytics environments with controlled access.

What we aim for​

Our data reporting approach is built around a few core principles:

  • Consistency so teams interpret metrics in the same way
  • Traceability so important figures can be traced back to their source
  • Validation so incorrect or incomplete data is identified early
  • Controlled access so only authorized users can view sensitive datasets

These principles also support compliance with PIPEDA and vendor data-processing obligations where applicable.

Data flow overview​

Data moves through a structured pipeline from raw systems into trusted reporting outputs used for operations and decision-making.

Source systems​

Operational systems generate logs, metrics, and events used for both day-to-day operations and long-term analysis.

Processing and validation​

Data is standardized and checked for accuracy and completeness before being used in reporting layers. This reduces inconsistencies between teams and systems.

Reporting layer​

The reporting layer provides controlled, trusted datasets used for dashboards, operational monitoring, and decision-making.

Types of reporting insight​

EventLinx uses different categories of reporting depending on purpose:

Operational insights focus on real-time system health and availability, while longer-term analytics support planning and product improvement. Security-related signals may also be incorporated into monitoring systems as described in our auditing and monitoring strategy.

Data quality and validation​

We apply automated and procedural checks to ensure data reliability. This includes detecting missing fields, inconsistent values, or anomalies that may indicate system or input errors. Issues are tracked and resolved through standard engineering and maintenance workflows.

Access and governance​

Access to reporting systems is role-based, logged, and restricted to authorized personnel. External vendors or processors are managed under our third-party management framework.

Where personal information appears in datasets, EventLinx prioritizes aggregation and de-identification wherever possible, especially for secondary or analytical use cases.

Compliance alignment (conceptual)​

EventLinx data handling practices align with PIPEDA requirements for limiting use, protecting data, and controlling access. While external standards such as healthcare-oriented frameworks (e.g., OMOP-style models or terminology systems like SNOMED CT, LOINC, RxNorm) are referenced in industry discussions, they are not formally adopted here unless explicitly stated in system documentation.

These references are included for conceptual alignment only.