1. Employee Data Analysis using Excel
1
STUDENT NAME : DINESH KUMAR G
REGISTER NO : unm203bcm22078
DEPARTMENT :COMMERCE
COLLEGE : K.C.S. KASI NADAR COLLAGE OF ARTS & SCEINCE
3. AGENDA
1. Problem Statement
2. Project Overview
3. End Users
4. Our Solution And Proposition
5. Dataset Description
6. Modelling Approach
7. Results And Discussion
8. Conclusion
4. PROBLEM STATEMENT
4
THE PROBLEM IS TO IDENTIFY THE EMPLOYEES
DATA ACCORDING THEIR Employee name ,Employee
ID, Department, Gender, Recruitment Source, Salary per
month .
5. PROJECT OVERVIEW
5
IN THIS ANALYSIS IM GOING TO EASE THE PROCESS OF IDENTIFY
THE EMPLOYEES SALARY,RECRUITMENT SOURCE,DEPARTMENT
USING EXCEL, WITH THE HELP OF BELOW MENTIONED TOOLS IN
EXCEL.
TABLES.
SLICERS.
PIVOT CHART(LINE CHART,PIE CHART & BAR CHART).
CONDITIONAL FORMATTING
6. WHO ARE THE END USERS?
6
A. Human Resources (HR) Department
B. Finance Department
C. Compensation and Benefits Specialists
D. Operational Managers
E. IT and Data Management Teams
7. OUR SOLUTION AND ITS VALUE PROPOSITION
7
User-Friendly Interface:
•Accessibility
•Ease of Use
Comprehensive Data Management:
•Data Organization
•Data Integration
Advanced Analytical Tools:
•Formulas and Functions
•PivotTables
Visual Representation:
•Charts and Graphs
Scenario Analysis:
Used to analyse different situation
8. Dataset Description
Data Overview:
The dataset contains information about
employees within an organization, This data is
used to calculate and analyze the project progress
metrics.
Data Fields:
1. Employee name
2. Employee ID
3. Department
4. Gender
5. Recruitment Source
6. Salary per month
9. 3/21/2024 Annual
Review
THE "WOW" IN OUR SOLUTION
9
I. Dynamic Dashboards
II. Advanced Data Visualization
III. Segmentation Analysis
IV. Comparative Analysis
V. Interactive Reports
VI. Slicers
10. 10
MODELLING
i. Data cleaning.
ii. Creating table.
iii. Creating pivot chart.
iv. Creating dashboard.
v. Inserting pivot chart in dashboard.
vi. Creating interactive dashboard by putting all
together elements.
12. conclusion
The employee data analysis highlights significant disparities
and provides actionable insights for refining compensation
strategies, improving equity, and enhancing overall
departmental performance. By addressing these findings, the
organization can better align its compensation practices with
its strategic objectives and improve employee satisfaction and
retention.
