Create:
Monthly_Sales_Data_Consolidation.xlsx
Source Files
Create three datasets:
- January_Sales
- February_Sales
- March_Sales
Example:
|
Order ID |
Date |
Customer |
City |
Product |
Qty |
Sales |
|
J001 |
05-Jan-26 |
Amit |
Sirsa |
Laptop |
2 |
120000 |
|
J002 |
08-Jan-26 |
Neha |
Hisar |
Mouse |
10 |
5000 |
|
J003 |
15-Jan-26 |
Rahul |
Sirsa |
Monitor |
3 |
102000 |
|
J004 |
21-Jan-26 |
Priya |
Fatehabad |
Keyboard |
8 |
6400 |
Repeat similar data for February and March.
Project Tasks
Step 1 — Import
Import all three monthly datasets using Power Query.
Step 2 — Clean
- Rename columns
- Remove unnecessary columns
- Change data types
- Remove duplicates
- Replace incorrect city names
- Handle blank values
Step 3 — Transform
- Split columns where required
- Merge columns where required
- Fill Down missing categories
- Filter invalid records
- Sort data
Step 4 — Combine
Use:
Append Queries
to combine:
January + February + March
Step 5 — Merge
Merge the combined sales query with a Product Master table.
Step 6 — Create Columns
Create:
Profit
Sales – Cost
and:
Sales Category
High / Normal / Low
Step 7 — Group By
Create:
City-wise Total Sales
and:
Product-wise Total Sales
Step 8 — Load
Load the final cleaned dataset into:
Clean_Sales_Data
Step 9 — Refresh Test
Add a new April record to the source and refresh the query.
Verify that the consolidated dataset updates.
FINAL PROJECT OUTPUT
Your workbook should contain:
- January_Sales
- February_Sales
- March_Sales
- Product_Master
- Q_January
- Q_February
- Q_March
- Q_Combined_Sales
- Q_Final_Clean_Data
- Sales_Summary
Final Summary
|
City |
Total Sales |
Total Orders |
|
Sirsa |
— |
— |
|
Hisar |
— |
— |
|
Fatehabad |
— |
— |