Utility Meter-to-Bill Reconciliation Dataset
Compare cumulative meter-reading differences with invoiced energy units.
A practical workbook exercise for billing analysts and utility operations. Work from the underlying records, compare the relevant totals and explain how you reached your result.
About the dataset
This original synthetic dataset contains 240 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Energy and utilities |
| Formats | Excel workbook and CSV files |
| Source records | 240 |
| Related tables | 3 |
| Fields across table schemas | 13 |
| Reporting cutoff | September 30, 2026 |
| Currency | USD for monetary fields |
| Source | Original synthetic data created for Jolene.pro Workbook Studies |
What's included
- Meters: 30 records and 4 fields. One meter with a fixed USD rate per kWh.
- Readings: 120 records and 4 fields. One cumulative month-end reading.
- Bills: 90 records and 5 fields. One monthly energy bill.
Recommended analysis
- Which bills differ from the meter-reading change?
- What is the USD value of those unit differences?
- Are any reading sequences decreasing or duplicated?
- Why must cumulative readings not be summed as consumption?
How to work with the data
Use the following relationships to connect the source tables:
- Readings.meter_id → Meters.meter_id
- Bills.meter_id → Meters.meter_id
Check the row grain before joining. Aggregate repeated child records to the required level before combining totals, so parent amounts are not counted more than once.
You can explore the workbook in Excel or Jolene.pro, or use the CSV files with SQL, Power BI and other analysis tools.
Definitions and assumptions
- Opening reading is June 30. Billing covers July through September. No meter resets, estimated readings or standing charges are modeled.
- Some invoiced units intentionally differ from meter deltas. Report the exception without asserting wrongdoing.
Use the field definitions and nullable-column guidance in the included data dictionary. Interpret blank values and reporting dates according to the scenario notes.
Downloads
The complete dataset ZIP includes the Excel workbook, three matching CSV files, a data dictionary, scenario notes, a source-row preview and license details.
Reuse and attribution
These are synthetic records, not customer data or industry benchmarks. Reuse is allowed under Creative Commons Attribution 4.0 International (CC BY 4.0). Credit Jolene.pro and identify any changes you make.