Employee Leave Balance Ledger
This dataset provides a detailed, period-based ledger of employee leave accruals, usage, and balances across multiple leave types and departments. It supports compliance monitoring, resource planning, and trend analysis for HR teams, offering granular visibility into workforce availability and leave patterns.
Sample rows
preview · 8 of 62 rows · all 12 columns| employee_idstring | leave_typestring | leave_accruedfloat | manager_idstring | employee_namestring | departmentstring | period_start_datedate | period_end_datedate | leave_usedfloat | leave_balancefloat | last_updateddatetime | statusstring |
|---|---|---|---|---|---|---|---|---|---|---|---|
| E1001 | annual | 1.5 | E1005 | Maria Chen | Finance | 2024-01-01 | 2024-01-31 | 0.5 | 12.5 | 2024-02-01T09:17:00 | active |
| E1002 | sick | 0 | E1003 | David Singh | Engineering | 2024-01-01 | 2024-01-31 | 1 | 3 | 2024-02-01T11:20:25 | active |
| E1003 | annual | 2 | E1008 | Sarah Albright | Engineering | 2024-01-01 | 2024-01-31 | 1 | 14 | 2024-02-01T10:45:09 | active |
| E1004 | parental | 0 | E1006 | John O'Brien | Marketing | 2024-01-01 | 2024-01-31 | 5 | 5 | 2024-02-01T09:50:11 | on leave |
| E1005 | annual | 1.5 | E1010 | Priya Kapoor | Finance | 2024-01-01 | 2024-01-31 | 0 | 17.5 | 2024-02-01T08:23:42 | active |
| E1006 | sick | 0 | E1011 | Linda Gomez | Marketing | 2024-03-01 | 2024-03-31 | 2 | 1 | 2024-04-01T10:00:00 | active |
| E1007 | unpaid | 0 | E1012 | Yusuf Ahmed | HR | 2024-01-15 | 2024-01-20 | 3 | 10 | 2024-01-21T15:27:10 | on leave |
| E1008 | annual | 2 | E1002 | Emma Johansson | Engineering | 2024-02-01 | 2024-02-28 | 0 | 20 | 2024-02-29T09:10:10 | active |
| E1009 | sick | 0 | E1015 | Lucas Müller | Operations | 2024-02-05 | 2024-02-07 | 2 | 2 | 2024-02-08T08:00:00 | on leave |
| E1010 | other | 0 | E1001 | Olivia Brown | Finance | 2024-03-01 | 2024-03-15 | 1 | 0 | 2024-03-16T14:20:00 | active |
| E1011 | annual | 1.5 | E1007 | Chen Wang | HR | 2024-02-01 | 2024-02-28 | 0.5 | 8 | 2024-02-29T13:05:45 | active |
| E1012 | parental | 0 | E1014 | Karen Dubois | HR | 2024-01-01 | 2024-01-31 | 10 | -2 | 2024-02-01T10:00:00 | on leave |
| E1013 | annual | 2 | E1009 | Tariq Hassan | Operations | 2024-03-01 | 2024-03-31 | 2 | 10 | 2024-04-01T10:33:00 | active |
| E1014 | annual | 2 | E1003 | Natalie Evans | Engineering | 2024-04-01 | 2024-04-30 | 0 | 15 | 2024-05-01T09:00:00 | active |
| E1015 | sick | 0 | E1009 | Samuel Park | Operations | 2024-03-20 | 2024-03-21 | 1 | 3 | 2024-03-22T13:30:00 | on leave |
| E1016 | annual | 1.5 | E1005 | Jessica Lee | Finance | 2024-02-01 | 2024-02-28 | 1.5 | 6 | 2024-02-29T15:00:00 | active |
| E1017 | annual | 2 | E1003 | Andreas Schmidt | Engineering | 2024-03-01 | 2024-03-31 | 0 | 18 | 2024-04-01T11:00:00 | active |
| E1018 | unpaid | 0 | E1015 | Alina Petrova | Operations | 2024-04-10 | 2024-04-12 | 2 | 8 | 2024-04-13T08:30:00 | on leave |
| E1019 | sick | 0 | E1012 | Mohamed Farouk | HR | 2024-01-10 | 2024-01-11 | 2 | 1 | 2024-01-12T11:20:00 | on leave |
| E1020 | parental | 0 | E1001 | Sofia Rossi | Finance | 2024-01-01 | 2024-01-31 | 4 | -1 | 2024-02-01T14:30:00 | on leave |
What the 62 rows show
from the 62-row sampleAnnual (leave type) stands out: mean leave_
- 1.5median leave_
accrued - 2statuses
- 7departments
- 1.0median leave_
used - 6.8median leave_
balance
Median 1.5, from 0.0 to 2.1.
- string 6
- float 3
- date 2
- datetime 1
Columns
12 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 6 columns | |||
employee_id | string | Unique identifier for each employee | E1001 |
employee_name | string | Full name of the employee | Maria Chen |
department | string | Department or business unit the employee belongs to7 departments | Finance |
leave_type | string | Type of leave (e.g., annual, sick, parental, unpaid)annual · sick · parental · unpaid · other | annual |
manager_id | string | Unique identifier of the employee's manageroptional | E1005 |
status | string | Employment status during the period (e.g., active, on leave, terminated)active · on leave · terminated | active |
| Numbers 3 columns | |||
leave_accrued | float | Amount of leave accrued during the period (in days or hours)0 or more | 1.5 |
leave_used | float | Amount of leave used during the period (in days or hours)0 or more | 0.5 |
leave_balance | float | Current available leave balance at the end of the period (in days or hours) | 12.5 |
| Dates and times 3 columns | |||
period_start_date | date | Start date of the leave accrual or usage period | 2024-01-01 |
period_end_date | date | End date of the leave accrual or usage period | 2024-01-31 |
last_updated | datetime | Timestamp when the record was last updated | 2024-02-01T09:17:00 |
Use it for
A human resources dashboard
Leave_
accrued by leave_ type and a breakdown of manager_ id. Excel, Power BI or Tableau. Why do the 32 annual rows have a mean leave_
accrued of 1.9? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Employees62E10011.5annualE10020sickE10032annual
A software demo
Believable employees with employee_
name, department and leave_ type to fill a screen in front of a buyer.
blueprint · employee-leave-balance-ledger
Behind this dataset
Same schema. As many rows as you need.
These 62 rows came out of a blueprint — 12 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
- Initial balance loaded from HR system
- All leave requests must have approval status
- Accrual calculated monthly
- Balances cannot go negative
- Flag overdrawn leave for HR review
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- employee-leave-balance-ledger