HR Data Analysis
Using PowerBI
In this project, Designed a Power BI dashboard to track employee data for the HR team, including working hours, attendance, performance, and leaves. The dashboard streamlined HR processes and increased efficiency.
ABOUT DATA
This Dataset includes various employees, their unique employee codes, and their attendance status for each day.
The attendance status is represented by different codes, such as "P" for the present, "WFH" for work from home, "SL" for sick leave, and others. The dataset also includes additional codes for paid leave, half-day leave, floating festival leave, birthday leave, bereavement leave, and more.
The data is organized in a tabular format with columns representing each day of the selected period. Each row corresponds to a specific employee, and their attendance status is recorded for each day.
DATA CLEANING AND PREPROCESING
Data cleaning and preprocessing:
Open power bi and transform data
Make sure first row as header
Select emp_id, name and unpivot other columns
Rename column name and change datatype also remove error.
Create parameter and function:
Open power bi and transform data
Make first row as header
Select emp_id, name and unpivot other columns
Rename column name and change datatype also remove error.
Step by step data cleaning process - Watch following Video.
DATA ANALYSIS
Order vs Sales :
Create pivot table
Add Months, Amount, Order_Id in the pivot table
Go to the insert tab and click on the pivot chart option
Next, select the clustered column-line chart and use the secondary axis option
Orders - Channels :
Create pivot table
Add Channel, Order_Id in the pivot table
Go to the insert tab and click on the pivot chart option
Next, select the column chart and edit it.
Purchase- men vs Women :
Create pivot table
Add Gender, Amount in the pivot table
Go to the insert tab and click on the pivot chart option
Next, select Pie chart and edit it.
Order Status :
Create pivot table
Add status, Order_Id in the pivot table
Go to the insert tab and click on the pivot chart option
Next, select the Pie chart and edit it.
Top 5 Sales State :
Create pivot table
Add Ship_State, Amount in the pivot table
Go to the insert tab and click on the pivot chart option
Next, select the Horizontal Bar chart and edit it.
Highest Selling Category :
Create pivot table
Add Category, Amount, Order_Id in the pivot table
Go to the insert tab and click on the pivot chart option
Next, select the clustered column-line chart and use the secondary axis option
Orders- Age vs Gender :
Create pivot table
Add Age_Group, Amount in the pivot table
Go to the insert tab and click on the pivot chart option
Next, select the clustered column chart and go to the format chart area and add percentages.
Vrinda Store Data Analysis Video
REPORT
Create a new sheet for the report section.
Copy and paste all pivot charts from other sheets to the report sheet.
Add slicers Months, Channel, Category, and Connect to all pivot charts.
Arrange all pivot charts in a suitable format.
Vrinda Store Workbook Here Click Please to view.
INSIGHTS
Top sales in march month.
The women's purchase rate is high.
The delivered Status is 92%.
The top 3 states are Maharashtra, Karnataka, and Uttar Pradesh.
The top purchased category is "Set".
Most sales in women, in each category.
Maximum sales by amazon are 35%.
CONCLUSION
Target women customers of age group (30-49 yrs) living in Maharashtra, Karnataka and Uttar Pradesh by showing ads/offers/coupons available on Amazon, Flipkart and Myntra.
Vrinda Store Analysis PPT
In this PPT, we analyze the Vrinda store data annual sales report for 2022.
How to download and use material :
1) Go to the following link.
2) Download and Open the HR_Analytics_Data.xlsx file in Excel.
3) Open PowerBI, Import the above data and continue working on that in power bi using HR_Analytics_Notes.
4) Make Visualization and Interactive Dashboard.