๐ Hierarchical and Parametric Analytical Reporting >> Data segmentation and Granularity
๐ Hierarchical and Parametric Analytical Reporting >> Data segmentation and Granularity
The data segmentation in this application ensures maximum granularity and traceability by defining a unique key for every single record, integrating both the organizational structure and the temporal dimension.
Every data record is precisely identified by the following six key attributes:
Asset Name : Identifies the physical asset or primary category (e.g., equipment, vehicle fleet, or a specific site/location) associated with the incident data.
Unit Name : Specifies the intermediate organizational unit or department responsible for the Asset. This helps in departmental reporting and accountability.
Node Name): Defines the lowest level of the organizational hierarchy being tracked (e.g., a specific team, section, or cost center). This is the key element for hierarchical analysis.
Reference Year: Defines the fiscal or calendar year to which the data belongs, crucial for historical comparison.
Reference Month : Defines the specific month within the year, allowing for monthly calculation, reporting, and precise trend analysis.
Data Source: Identifies where the data originated (e.g., manual entry, imported file, or automatic system feed). This is essential for auditing and validating the integrity of the input.
This robust segmentation ensures that all calculated indices (FR and SR) can be precisely filtered, aggregated, and visualized across any combination of time, organizational structure, and data input method, facilitating accurate hierarchical analytical reporting and comprehensive asset auditing.