Human Resources
29 columns
200 rows
8 formats

Enterprise Employee Attrition Events

This dataset provides comprehensive records of enterprise employee attrition events, detailing voluntary and involuntary exits with contextual information such as tenure, performance, exit reasons, and retention actions. It is ideal for modeling attrition trends, analyzing workforce turnover, and developing targeted retention strategies to improve organizational stability.

last updated 5 Sept 2025
by GoMask

The brief that made it

Attrition modeling and prediction

Sample rows

preview · 8 of 200 rows · all 29 columns

event_idstring	exit_reasonstring	severance_paidfloat	eligible_for_rehireboolean	genderstring	employee_idstring	first_namestring	last_namestring	date_of_birthdate	hire_datedate	exit_datedate	departmentstring	job_titlestring	location_citystring	location_statestring	location_countrystring	manager_idstring	exit_typestring	exit_sub_reasonstring	tenure_yearsfloat	age_at_exitinteger	performance_ratinginteger	salaryfloat	exit_interview_completedboolean	last_day_workeddate	notice_period_weeksinteger	retention_offer_madeboolean	retention_offer_acceptedboolean	exit_interview_notesstring
EVT0001	Resignation	0	true	Female	EMP001	Olivia	Chen	1992-08-14	2018-06-01	2024-02-15	Engineering	Software Developer	San Francisco	CA	USA	MGR101	Voluntary	Accepted offer at another tech firm	5.7	31	4	124000	true	2024-02-14	4	true	false	Olivia expressed appreciation for her team and cited career growth as her reason for leaving.
EVT0002	Retirement	16000	false	Male	EMP002	Lucas	Smith	1987-05-23	2010-03-12	2024-04-01	Finance	Senior Accountant	London	blank	UK	MGR102	Voluntary	Reached retirement eligibility age	14.1	36	5	89000	true	2024-03-29	8	false	false	Lucas retired after many years of service and was commended for his dedication.
EVT0003	Other	0	true	Female	EMP003	Priya	Kumar	1998-12-05	2023-06-19	2023-12-20	Support	Intern	Mumbai	blank	India	MGR103	Voluntary	End of internship program	0.5	25	4	0	true	2023-12-20	0	false	false	Priya completed her internship successfully and may apply for full-time roles.
EVT0004	Termination	0	false	Male	EMP004	Daniel	Miller	1995-01-11	2020-10-15	2023-10-30	Sales	Sales Representative	Houston	TX	USA	MGR104	Involuntary	Performance below expectations	3	28	1	45000	false	2023-10-29	0	false	false	blank
EVT0005	Resignation	0	true	Female	EMP005	Samantha	Williams	1983-03-07	2012-05-22	2022-08-31	Human Resources	HR Manager	Sydney	NSW	Australia	MGR105	Voluntary	Relocated to another country	10.3	39	5	102000	true	2022-08-30	6	true	false	Samantha left for personal reasons and was a valued team member.
EVT0006	Retirement	25000	false	Male	EMP006	Mohamed	Ali	1969-11-12	2005-01-03	2023-03-31	Operations	Operations Director	Cairo	blank	Egypt	MGR106	Voluntary	Retiring after long career	18.2	53	4	78000	true	2023-03-30	10	false	false	Mohamed retired with honors and received a severance package.
EVT0007	Resignation	0	true	Female	EMP007	Emily	Johnson	1990-06-22	2019-04-10	2022-05-09	Marketing	Marketing Coordinator	New York	NY	USA	MGR107	Voluntary	Career change to a new industry	3.1	31	5	67000	true	2022-05-06	4	true	false	Emily sought new opportunities outside the company.
EVT0008	Layoff	10000	true	Male	EMP008	Ahmed	Hassan	1982-09-30	2015-07-16	2022-12-20	Facilities	Facilities Technician	Dubai	blank	UAE	MGR108	Involuntary	Workforce reduction due to restructuring	7.4	40	3	42000	false	2022-12-19	2	false	false	blank
EVT0009	Resignation	0	true	Non-binary	EMP009	Taylor	Evans	1996-04-10	2021-08-01	2023-01-15	Product	Product Analyst	Toronto	ON	Canada	MGR109	Voluntary	Pursuing graduate studies	1.5	26	4	51000	true	2023-01-13	2	false	false	Taylor left to pursue further education and is eligible for rehire.
EVT0010	Resignation	0	false	Male	EMP010	Chen	Wu	1989-11-19	2014-03-01	2023-11-30	Engineering	Senior Developer	Shanghai	blank	China	MGR110	Voluntary	Moved to a competitor company	9.8	34	5	98000	true	2023-11-30	4	true	false	Chen was offered a higher position at another company.
EVT0011	Resignation	0	true	Female	EMP011	Fatima	Rahman	1986-07-04	2011-09-21	2023-06-15	Customer Success	Customer Success Specialist	Abu Dhabi	blank	UAE	MGR111	Voluntary	Family relocation abroad	11.7	36	4	67000	true	2023-06-13	6	true	false	Fatima is moving overseas and leaves on good terms.
EVT0012	Retirement	30000	false	Male	EMP012	Ivan	Petrov	1972-02-19	2007-09-08	2023-09-30	Legal	Senior Counsel	Moscow	blank	Russia	MGR112	Voluntary	Retirement after extended tenure	16.1	51	5	185000	true	2023-09-29	12	false	false	Ivan retired and was recognized for his expertise.
EVT0013	Termination	0	false	Female	EMP013	Sarah	Lee	1999-03-10	2022-01-15	2022-11-18	Engineering	Junior Developer	Seoul	blank	South Korea	MGR113	Involuntary	Position eliminated due to project closure	0.8	23	2	29000	false	2022-11-17	0	false	false	blank
EVT0014	Resignation	0	true	Male	EMP014	Gabriel	Martinez	1988-04-21	2016-02-02	2022-03-10	Sales	Sales Manager	Mexico City	blank	Mexico	MGR114	Voluntary	Career advancement at another company	6.1	34	5	74000	true	2022-03-10	4	true	false	Gabriel moved for a higher level position elsewhere.
EVT0015	Resignation	0	true	Female	EMP015	Aisha	Abdullah	1991-09-17	2019-07-03	2023-02-01	Product	Product Specialist	Dubai	blank	UAE	MGR115	Voluntary	Personal reasons	3.6	31	4	64000	true	2023-01-31	4	false	false	Aisha left for family reasons and is open to future opportunities.
EVT0016	Termination	0	false	Male	EMP016	William	Brown	1997-12-30	2022-05-10	2023-01-09	Security	Security Officer	Berlin	blank	Germany	MGR116	Involuntary	Violation of company policy	0.7	25	1	32000	false	2023-01-09	0	false	false	blank
EVT0017	Layoff	16000	true	Female	EMP017	Hannah	Kim	1985-02-27	2012-04-20	2023-08-11	IT	IT Support Specialist	Seoul	blank	South Korea	MGR117	Involuntary	Department downsizing	11.3	38	3	59000	true	2023-08-10	2	false	false	Hannah was laid off due to restructuring and may be rehired.
EVT0018	Resignation	0	true	Male	EMP018	Noah	Clark	1980-06-11	2009-08-15	2023-07-01	Administration	Administrative Coordinator	Chicago	IL	USA	MGR118	Voluntary	Relocation to another state	13.9	43	4	61000	true	2023-06-30	6	true	false	Noah is moving to support family and may return in the future.
EVT0019	Resignation	0	true	Female	EMP019	Chloe	Nguyen	1994-11-20	2020-02-18	2023-10-31	Product	Product Coordinator	Paris	blank	France	MGR119	Voluntary	Pursuing a new opportunity in another field	3.7	29	4	67000	true	2023-10-30	4	false	false	Chloe is open to future roles and left amicably.
EVT0020	Termination	0	false	Male	EMP020	Ethan	Garcia	1993-02-15	2018-09-01	2023-03-15	Engineering	DevOps Engineer	Austin	TX	USA	MGR120	Involuntary	Repeated violation of security protocols	4.5	30	1	87000	false	2023-03-15	0	false	false	blank

What the 200 rows show

from the 200-row sample

Retirement (exit reason) stands out: mean severance_paid is 20,556, against 924.3 for the rest.

75%eligible_for_rehire = true
0median severance_paid
2exit types
13location states
16departments
23location countries

Mean severance_paid by exit_reason199 rows

severance_paid199 rows, in bands of 5,000

Median 0, from 0 to 30,000.

gender199 rows with a value · 1 left blank

Male97
Female91
Non-binary4
Prefer not to say4
Other3

29 columns by typefrom the column list below

string 15
integer 3
float 3
date 4
boolean 4

Columns

29 columns in four groups

blueprint · 29 columns
column	type	description	example
Text 15 columns
`event_id`	string	Unique identifier for each employee attrition eventunique	EVT0001
`employee_id`	string	Unique identifier for the employee who exited	EMP001
`first_name`	string	Employee's first name	Olivia
`last_name`	string	Employee's last name	Chen
`gender`	string	Employee's genderMale · Female · Non-binary · Other · Prefer not to say · optional	Female
`department`	string	Department where the employee worked	Engineering
`job_title`	string	Employee's job title at the time of exit	Software Developer
`location_city`	string	City of the employee's work locationoptional	San Francisco
`location_state`	string	State of the employee's work locationoptional	CA
`location_country`	string	Country of the employee's work locationoptional	USA
`manager_id`	string	Unique identifier for the employee's manageroptional	MGR101
`exit_type`	string	Type of exit: voluntary or involuntaryVoluntary · Involuntary	Voluntary
`exit_reason`	string	Reason for exit (e.g., resignation, retirement, termination, layoff)Resignation · Retirement · Termination · Layoff · Other	Resignation
`exit_sub_reason`	string	Detailed sub-reason for exit (e.g., personal reasons, performance, downsizing)optional	Family relocation abroad
`exit_interview_notes`	string	Summary notes from the exit interviewoptional	Olivia expressed apprecia…
Numbers 6 columns
`tenure_years`	float	Total years the employee worked at the company0 or more	5.7
`age_at_exit`	integer	Employee's age at the time of exit16 or more · optional	31
`performance_rating`	integer	Employee's last performance rating (e.g., 1-5 scale)1 to 5 · optional	4
`salary`	float	Employee's annual salary at the time of exit0 or more · optional	124000
`notice_period_weeks`	integer	Number of weeks of notice given prior to exit0 or more · optional	4
`severance_paid`	float	Amount of severance paid to the employee, if applicable0 or more · optional	0
Dates and times 4 columns
`date_of_birth`	date	Employee's date of birthoptional	1992-08-14
`hire_date`	date	Date when the employee was hired	2018-06-01
`exit_date`	date	Date when the employee exited the organization	2024-02-15
`last_day_worked`	date	Employee's last actual day worked (may differ from exit date)optional	2024-02-14
True or false 4 columns
`eligible_for_rehire`	boolean	Indicates if the employee is eligible for rehireoptional	true
`exit_interview_completed`	boolean	Indicates if an exit interview was completedoptional	true
`retention_offer_made`	boolean	Indicates if a retention offer was made to the employee prior to exitoptional	true
`retention_offer_accepted`	boolean	Indicates if the retention offer was acceptedoptional	false

Use it for

A human resources dashboard
The eligible_for_rehire rate, severance_paid by exit_reason and a breakdown of gender. Excel, Power BI or Tableau.
Why do the 18 Retirement rows have a mean severance_paid of 20,556?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Events200
EVT00010Resignat…
EVT000216000Retireme…
EVT00030Other
A software demo
Believable events with employee_id, first_name and last_name to fill a screen in front of a buyer.

This dataset200 rows29 columns

Yours1,000 rows29 columnslocation_city: UK only

blueprint · enterprise-employee-attrition-events

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 29 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.

Rules it was built with

Exit date, reason, and job role required.
Department and tenure tracked.
Voluntary resignations vs. layoffs specified.
Exit interview completed flag included.
Rehire eligibility noted.

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: enterprise-employee-attrition-events

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

A human resources dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Human Resources

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