Employee Skill Assessment Matrix
This dataset provides a detailed matrix mapping employee skill levels to job role requirements, enabling organizations to identify skill gaps, recommend targeted training, and optimize workforce alignment. It includes employee, job, and skill identifiers, assessment results, and training recommendations, making it ideal for HR analytics and talent development strategies.
Sample rows
preview · 8 of 45 rows · all 14 columns| employee_idstring | employee_skill_levelinteger | training_recommendedboolean | employee_namestring | departmentstring | job_role_idstring | job_role_titlestring | skill_idstring | skill_namestring | required_skill_levelinteger | skill_gapinteger | last_assessment_datedate | training_completedboolean | manager_idstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| E001 | 3 | true | Maria Chen | Engineering | JR101 | Software Engineer | SK201 | Python | 4 | 1 | 2024-04-20 | false | M012 |
| E001 | 4 | false | Maria Chen | Engineering | JR101 | Software Engineer | SK202 | SQL | 3 | -1 | 2024-04-20 | blank | M012 |
| E001 | 2 | true | Maria Chen | Engineering | JR101 | Software Engineer | SK203 | Agile Methodology | 3 | 1 | 2024-04-20 | true | M012 |
| E002 | 3 | false | James Smith | Product | JR102 | Product Manager | SK204 | Roadmapping | 3 | 0 | 2024-03-15 | blank | M010 |
| E002 | 2 | true | James Smith | Product | JR102 | Product Manager | SK205 | Stakeholder Management | 3 | 1 | 2024-03-15 | false | M010 |
| E002 | 3 | false | James Smith | Product | JR102 | Product Manager | SK206 | Jira | 2 | -1 | 2024-03-15 | blank | M010 |
| E003 | 2 | true | Aisha Patel | Marketing | JR103 | Marketing Analyst | SK207 | Google Analytics | 3 | 1 | 2024-02-10 | true | M014 |
| E003 | 3 | false | Aisha Patel | Marketing | JR103 | Marketing Analyst | SK208 | Market Research | 3 | 0 | 2024-02-10 | blank | M014 |
| E003 | 4 | false | Aisha Patel | Marketing | JR103 | Marketing Analyst | SK209 | Excel | 3 | -1 | 2024-02-10 | blank | M014 |
| E004 | 1 | true | Lucas Meyer | Finance | JR104 | Financial Analyst | SK210 | Financial Modeling | 3 | 2 | 2024-05-02 | false | M015 |
| E004 | 2 | false | Lucas Meyer | Finance | JR104 | Financial Analyst | SK211 | Excel | 2 | 0 | 2024-05-02 | true | M015 |
| E004 | 3 | false | Lucas Meyer | Finance | JR104 | Financial Analyst | SK212 | Power BI | 3 | 0 | 2024-05-02 | blank | M015 |
| E005 | 4 | false | Priya Khanna | Engineering | JR105 | DevOps Engineer | SK213 | AWS | 4 | 0 | 2024-04-01 | true | M012 |
| E005 | 3 | true | Priya Khanna | Engineering | JR105 | DevOps Engineer | SK214 | Docker | 4 | 1 | 2024-04-01 | true | M012 |
| E005 | 2 | true | Priya Khanna | Engineering | JR105 | DevOps Engineer | SK215 | Linux | 3 | 1 | 2024-04-01 | false | M012 |
| E006 | 3 | false | Sven Bergström | Human Resources | JR106 | HR Specialist | SK216 | Recruitment | 3 | 0 | 2024-03-11 | true | M016 |
| E006 | 2 | true | Sven Bergström | Human Resources | JR106 | HR Specialist | SK217 | Onboarding | 3 | 1 | 2024-03-11 | false | M016 |
| E006 | 3 | false | Sven Bergström | Human Resources | JR106 | HR Specialist | SK218 | HRIS | 2 | -1 | 2024-03-11 | blank | M016 |
| E007 | 3 | true | Robert Turner | Operations | JR107 | Operations Lead | SK219 | Process Improvement | 4 | 1 | 2024-05-12 | false | M017 |
| E007 | 2 | true | Robert Turner | Operations | JR107 | Operations Lead | SK220 | Supply Chain | 3 | 1 | 2024-05-12 | false | M017 |
What the 45 rows show
from the 45-row sample- 49%training_
recommended = true - 3median employee_
skill_ level - 9departments
- 3median required_
skill_ level - 0median skill_
gap
Median 3, from 1 to 4.
- string 8
- integer 3
- date 1
- boolean 2
Columns
14 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 8 columns | |||
employee_id | string | Unique identifier for each employee | E001 |
employee_name | string | Full name of the employee | Maria Chen |
department | string | Department or team the employee belongs to9 departments · optional | Engineering |
job_role_id | string | Unique identifier for the job role | JR101 |
job_role_title | string | Title of the job role | Software Engineer |
skill_id | string | Unique identifier for the skill | SK201 |
skill_name | string | Name of the skill being assessed | Python |
manager_id | string | Unique identifier for the employee's manageroptional | M012 |
| Numbers 3 columns | |||
employee_skill_level | integer | Current skill level of the employee for this skill (e.g., 1=Beginner, 2=Intermediate, 3=Advanced, 4=Expert)1 to 4 | 3 |
required_skill_level | integer | Skill level required for the employee's job role for this skill (e.g., 1=Beginner, 2=Intermediate, 3=Advanced, 4=Expert)1 to 4 | 4 |
skill_gap | integer | Difference between required skill level and employee's current skill level (positive means upskilling needed) | 1 |
| Dates and times 1 column | |||
last_assessment_date | date | Date when the employee's skill was last assessedoptional | 2024-04-20 |
| True or false 2 columns | |||
training_recommended | boolean | Indicates if training is recommended for this skill based on the skill gap | true |
training_completed | boolean | Indicates if the employee has completed recommended training for this skilloptional | false |
Use it for
A human resources dashboard
The training_
recommended rate, employee_ skill_ level and a breakdown of employee_ id. Excel, Power BI or Tableau. Why do 22 of 45 rows have training_
recommended = true? A class exercise
Hand out the rows and one question. Everyone works from the same 45 rows.
- Employees45E0013trueE0014falseE0012true
A software demo
Believable employees with employee_
name, department and job_ role_ id to fill a screen in front of a buyer.
blueprint · employee-skill-assessment-matrix
Behind this dataset
Same schema. As many rows as you need.
These 45 rows came out of a blueprint — 14 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.
- List skills for each employee
- Assign proficiency rating per skill
- Match employees to job skill needs
- Flag skill gaps over two levels
- Suggest training for gaps
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
- employee-skill-assessment-matrix