Data Quality Tracking
Abisko provides comprehensive dashboards and reports that highlight data quality and completeness for every meter, property, group, and portfolio.- Meter-level: Gaps, data completeness (%), overlaps, monthly & annual jumps
- Property level: Issues summary, data completeness (%), data coverage (%), monthly & annual jumps, high & low values
- Portfolio-level: Issues summary, data completeness (%), data coverage (%), annual jumps
Data quality insights are included with every reported performance metric to provide users with a clear and immediate assessment of reporting readiness.
Data Quality Calculations
The following general algorithm is used for calculating data quality metrics at the meter, property and portfolio levels:1
Daily values are derived from each utility meter entry
Analytics break down every single utility meter entry into individual days.
2
A time-based window is applied to data for each individual meter
Data from each meter is included based on the meter’s activation dates and the property’s ownership period, ensuring that only relevant data is used in reporting.
3
Individual daily gaps and overlaps are calculated for each meter
Every missing and overlapping day (gaps & overlaps) between all entries for each meter is identified and indexed over all time.
4
Monthly values for consumption, gaps, and overlaps are calculated for each meter
Individual daily values are aggregated to provide monthly consumption, gap and overlap totals for each calendar month to normalize staggered utility data entries.
5
Secondary data quality metrics are calculated for each meter
Normalized consumption and gap values are analyzed to determine monthly data completeness (%) and monthly jumps.
6
Rolling 12-month period data is aggregated for each meter
Monthly normalized values are aggregated to provide annual consumption and data completeness (%) values for every reporting period.
7
Property-level data quality metrics are calculated.
Monthly and annual consumption and data quality values are aggregated across all meters of a property by utility type and subtype (e.g. Total Energy, Electricity, Fuel, DHC, Direct Emissions Indirect Emissions, Water, Waste, etc.)
8
Values are further rolled up into portfolio-level insights.
Monthly and annual consumption and data quality values are aggregated across all properties in a portfolio.
Learn More
Data Completeness
Understand the extent of missing utility data over any reporting period.
Gaps, Overlaps and Jumps
Identify specific periods of missing data to take targeted action.
Outliers & Benchmarks
Identify properties that have unusually high or low intensity values.
EXCEL Reports
Export reports that detail data quality issues across a portfolio.