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Data Checker | BIM Analytics for Design Managers

Data quality is as critical as geometry in Building Information Modelling (BIM)

For Design Managers, ensuring that every model element carries complete, consistent, and accurate data is essential for coordination and downstream uses like cost estimation, planning, and facility management.

Why BIM Data Checks Matter?

Attributes or properties data in BIM models define the behavior, classification, and lifecycle information. Missing or incorrect data can cause:

  • Miscommunication between disciplines and stakeholders
  • Inaccurate quantity take-offs and, thereby, estimates
  • Delays in project approvals due to unclear scope
  • Design changes
  • Cost and time overruns

BIM Data Checker - How to read data?

The BIM Data Checker module provides a powerful tool for Design Managers to run automated validation checks against model properties. Here’s how it supports design quality:

  • Comprehensive Property Data Validation

The dashboard shows 592 Required Properties tracked for Slabs

100% of Elements Have Values for defined properties (e.g., Area, Perimeter, Thickness, Volume) as per the guidelines

  • Breakdown of Data by Category and Property

Design Managers can filter data and elements by category (e.g., slabs, walls) and property type to inspect data completeness per element.

Example from the interface: Slabs have 148 elements, with 100% having values and proper value types for all key parameters.

  • Visual Feedback for Quick Analysis of missing or incomplete data

Gauges and percentage bars provide instant feedback on data health. Visual flags missing or incorrect values visually, helping teams act faster.

  • Model Integration

The 3D model viewer allows design managers to inspect properties in context, ensuring alignment between data and geometry.

  • Support for Standardization

Supports defining standard property formats, pick lists, and acceptable value ranges to enforce data standards project-wide.

Benefits for Design Managers

  • Early detection of data gaps before coordination meetings
  • Assurance that models meet data requirements for BIM Execution Plans (BEP)
  • Better communication with quantity surveyors, planners, and contractors
  • Reduced risk of rework and project delays

Conclusion

With tools like BIM Data Checker, Design Managers gain visibility and control over model data quality, paving the way for truly integrated and reliable BIM workflows.

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