Use cases
Electrical Network Data Quality Control and Compliance Validation
Network operators, utilities and local authorities rely on accurate data to locate assets, plan maintenance activities, manage incidents and coordinate network upgrades.
Dotic solutions are built on a unique combination of industry expertise and data governance know-how. By combining deep knowledge of electrical network operations with advanced GIS data management capabilities, Dotic helps organisations improve data quality, strengthen compliance and maintain trusted network information throughout the asset lifecycle.
In practice, electrical network data is often compiled from multiple sources, including design studies, construction projects, field surveys and legacy network records. As a result, data quality issues are common, ranging from inaccurate asset locations and topological inconsistencies to incomplete or outdated asset attributes.
At the same time, growing industry requirements for structured, accurate and interoperable network data are raising expectations around data quality, governance and compliance.
In this context, data quality control has become an essential process for ensuring that network information remains reliable, operationally usable and fit for integration into GIS, asset management and operational systems.
Geospatial Data at the Heart of Network Safety and Operations
In electrical networks, geospatial data is far more than a mapping tool.
It directly supports:
- The safety of field operations
- The accurate location of live assets and network equipment
- The understanding of network connectivity and electrical configurations
- The management of outages, switching operations and isolations
- The maintenance and long-term management of infrastructure assets
Inaccurate or incomplete data can lead to significant operational risks, increased intervention costs and reduced network reliability.
Unlike many other infrastructure networks, electrical systems depend on highly accurate and consistent data from the earliest stages of operation. Reliable geospatial information is therefore essential for ensuring safe, efficient and effective network management.
Data from Multiple Sources and Stakeholders
Electrical infrastructure projects involve a wide range of stakeholders, including:
- Engineering and design consultancies
- Construction and installation contractors
- Surveying teams
- Network operators and asset owners
Each stakeholder creates, updates or enriches network data at different stages of the project lifecycle.
To support consistency and interoperability, industry data models and standards have been developed to structure information exchanges and provide a common framework for representing network assets from design and construction through to as-built delivery and operational use.
In practice, however:
- Data is not always produced or maintained consistently across organisations
- Levels of data structure and completeness can vary significantly
- Information may be lost, altered or duplicated as projects move between phases and stakeholders
The result is often data that is difficult to integrate into GIS and asset management systems, limiting its operational value and creating additional work for network operators.
Identify Anomalies in Electrical Network Data
Data quality control helps identify issues that can directly affect the operation, maintenance and management of electrical networks.
Common data quality issues include:
- Topological inconsistencies between substations, service cabinets, cables and connected assets
- Incorrect asset locations and positioning errors
- Missing technical attributes such as cable type, conductor size or voltage level
- Inconsistencies in service connections and network connectivity
- Data that does not comply with required network data models and quality standards
These issues can significantly reduce the operational value of network data, making it more difficult to use within GIS, asset management and other operational systems.
Identifying and resolving these anomalies is therefore essential to maintaining accurate, reliable and trusted network information.
Validate Data Compliance with Network Data Standards
Network data standards provide a common framework for structuring electrical network information and facilitating data exchange between stakeholders and operational systems.
They are designed to support:
- The modelling of electrical network assets and infrastructure
- The standardisation of technical and operational attributes
- Data consistency throughout the project lifecycle, from design and construction to operational use
However, a data standard alone does not guarantee data quality.
In practice:
- Data must be validated before being integrated into operational systems
- Inconsistencies and quality issues need to be identified as early as possible
- Data quality must be monitored throughout the entire project lifecycle
With Dotic solutions:
- Data is analysed at scale using ConnectControl and validation rules
- Deviations from required data models and specifications are automatically detected
- Data quality issues are classified and prioritised according to their impact
- Teams benefit from clear indicators and dashboards to monitor data quality over time
This approach helps organisations improve data reliability, strengthen compliance and ensure that network information is fit for operational use before it is integrated into GIS and asset management systems.
Automate Data Quality Control and Improve Reliability
Manual validation of electrical network data can be particularly challenging due to:
- The large number of assets and data objects involved
- Complex topological relationships between network components
- Stringent regulatory, operational and data quality requirements
With Dotic solutions:
- Data quality controls are automated through ConnectControl
- Validation rules tailored to electrical network requirements are applied consistently across datasets
- Data quality issues are automatically identified, located and visualised within ConnectServices
- Compliance and quality reports are generated to support validation and decision-making
By automating data quality control, organisations can improve data reliability, reduce validation times and ensure that network information remains accurate, consistent and ready for operational use.
Connect Data Quality Control to Field Reality
In electrical networks, maintaining a strong connection between field operations and network data is essential to ensuring data accuracy and operational reliability.
With Dotic solutions:
- Data collected through ConnectField is integrated directly into the central system
- Discrepancies between field observations and GIS records can be identified quickly
- Corrective actions can be initiated as soon as issues are detected
- Field and office teams work from a shared and up-to-date network reference dataset
This continuous flow of information helps ensure that network records accurately reflect real-world infrastructure, improving both data quality and operational confidence.
Secure Network Operations and Maintenance
A structured data quality control process helps organisations to:
- Improve the safety of field operations and interventions
- Increase the accuracy and reliability of network data
- Reduce errors and inconsistencies between field assets and digital records
- Support more efficient maintenance and asset management activities
- Ensure the quality and compliance of project deliverables
In electrical networks, data quality is not simply a data management concern—it is a fundamental requirement for maintaining network safety, operational efficiency and long-term infrastructure performance.
An Integrated Part of the Electrical Network Management Lifecycle
Data quality control is a fundamental process for ensuring the reliability of electrical network infrastructure and the safety of field operations.
As industry requirements for structured, accurate and interoperable network data continue to evolve, the ability to validate, improve and confidently use network information has become a key operational advantage for utilities, network operators and infrastructure owners.
By combining field-connected applications, GIS-based workflows and automated data quality controls, organisations can improve data reliability, strengthen operational safety and gain greater control over the management and performance of their electrical networks.
Managing Defects and Corrective Actions
- Identify defects and track corrective actions through to resolution
Intervention Planning and Progress Tracking
- Organise and Prioritise Corrective Actions in the Field
Final Work Acceptance and Handover Validation
- Validate Work Completion and Identify Field Defects
