Vessel Data Management
Modern vessels collect, transfer and store data from 1000s of sensors onboard. This connectivity provides a lot of opportunity, but also has hidden costs related to data management and storage. Collected Data need to be complete and of high quality, in order to avoid storing data which cannot be used to create value. Beyond storage costs, incomplete data sets can also lead to increased processing costs.
ADQM uses smart data evaluation
to ensure the immediate identification and alerting of sensor errors,
offer a simple overview of fleet data quality and
provide automatic tagging of data quality for further use.
Automatic Data Quality Management
Propulsion Analytics has developed the ADQM (Automatic Data Quality Management) system to automatically evaluate signal completeness and quality, in order to address the needs of shipping companies. The ADQM uses 4 consecutive & concurrent methods of data evaluation, including engineering logic, statistics and machine learning techniques, to automatically:
- Alert for sensors or signals that are problematic
- Provide an overview of data quality for any system, vessel or entire fleet through a simple UI
- Tag the saved data with quality and completeness KPIs
Most Effective Data Management
ADQM enables the vessel owners or managers to:
- Improve data quality through immediate alerts and automatic monitoring
- Reduce storage costs through selection & storage of complete data sets with high quality data
- Reduce data analysis costs through data tagging and ability to filter data based on quality and completeness