Create a workbook named:
Business_Dataset_Cleaning.xlsx
Raw Dataset
|
Order ID |
Date |
Customer |
City |
Product |
Category |
Qty |
Sales |
Payment |
|
O101 |
01-Sep-26 |
Amit |
Sirsa |
Laptop |
Electronics |
2 |
120000 |
Paid |
|
O102 |
02-Sep-26 |
Neha |
sirsa |
Mouse |
accessories |
10 |
5000 |
Paid |
|
O103 |
03-Sep-26 |
Rahul |
Hisar |
Laptop |
Electronics |
3 |
180000 |
Pending |
|
O104 |
04-Sep-26 |
Priya |
Fatebad |
Keyboard |
Accessories |
8 |
6400 |
Paid |
|
O105 |
05-Sep-26 |
Amit |
Sirsa |
Monitor |
Electronics |
4 |
34000 |
Paid |
|
O105 |
05-Sep-26 |
Amit |
Sirsa |
Monitor |
Electronics |
4 |
34000 |
Paid |
|
O106 |
06-Sep-26 |
Hisar |
Webcam |
Accessories |
4 |
10000 |
Pending |
|
|
O107 |
07-Sep-26 |
Simran |
HISAR |
Laptop |
electronics |
1 |
60000 |
Paid |
|
O108 |
08-Sep-26 |
Rahul |
Sirsa |
Mouse |
Accessories |
15 |
7500 |
Paid |
Project Tasks
- Sort data by Sales.
- Filter Sirsa records.
- Apply advanced filtering.
- Remove duplicate Order IDs.
- Standardize City names.
- Standardize Category names.
- Remove extra spaces using TRIM.
- Identify blank Customer values.
- Handle missing data.
- Create Payment drop-down.
- Apply Conditional Formatting.
- Highlight Sales > ₹50,000.
- Convert data into an Excel Table.
- Create named ranges.
- Check formula/data errors.
- Prepare a final Clean Business Dataset.
- Create a small summary showing:
- Total Sales
- Number of Orders
- Highest Sale
- Lowest Sale
- Pending Payments