# data[].attributes.body
Employee profile: name / id / address / contact
Department: department title / id
Training program member list: program id / participated id
Program list: id / Person In charge

# data[].attributes.body
Tables：
Staff info
Leave records
Salary history (basic salary、commission)
Payment Bank Acc.
Benefits(company)
Payroll Calculations formulas (EAO)

Link with：
Staff code

# data[].attributes.body
Employee informations： id number-> Phone number->employee number—> name , performance -> salary commissions, education.
Department_> service year

# data[].attributes.body
1.Receipt tracking number
2.data and time of receipt
3.Customer info
- Name
-phone number
-address
4.product/service included
5.handler
- Name
-staff id

# data[].attributes.body
employee's P-file:
- Name
-employee's staff ID
-address
-phone no.
-email
-emergency contact person
- bank account

appraisal
- Name
-employee's staff ID
-appraisal grade
- reward method

payroll
- Name
- employee's staff ID
- bank account
-appraisal grade > c&b package/ reward

# data[].attributes.body
Employee ID record (linked to):
1. Age
2. Gender
3. Salary
4. Education record
5. Working experience (linked to):
a. Performance record
b. Skills record
c. Training record

# data[].attributes.body
staff to further study:
1. name
2. department
3. education history
4. working experience
5. age
6. appraisal record(grade level)
7. gender

# data[].attributes.headline
DRIVER AND CAR TABLE: Driver  license Number, Drivers name, Car Number, Street address, City, State, Zip, Expiration Date, Car Make and year (Group1)

# data[].attributes.subject
DRIVER AND CAR TABLE: Driver  license Number, Drivers name, Car Number, Street address, City, State, Zip, Expiration Date, Car Make and year (Group1)

# data[].attributes.body
Employee education background -> employees’ name ->school name -> education level-> major/subject