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= Module 6: Summary and Final Exercises =  | |||
== Objective ==  | |||
Apply your Power Query skills in realistic, open-ended scenarios.  | |||
== Files Used ==  | |||
* [[Media:Sales_January.xlsx|Download Sales_January.xlsx]]  | |||
* [[Media:Sales_February.xlsx|Download Sales_February.xlsx]]  | |||
* [[Media:Employees.csv|Download Employees.csv]]  | |||
== Final Exercise 1: Combine and Analyze Sales Data ==  | |||
'''Goal:''' Merge January and February sales data and calculate revenue by region.  | |||
'''Steps:'''  | |||
# Load both files into Power Query: '''Sales_January.xlsx''' and '''Sales_February.xlsx'''  | |||
# Use '''Home''' tab → '''Append Queries'''  | |||
# Remove any unnecessary columns  | |||
# Ensure data types are correct  | |||
# Group by '''Region''' and sum '''Total Sales'''  | |||
# Sort results by total revenue  | |||
== Final Exercise 2: Filter Active Employees ==  | |||
'''Goal:''' Filter active employees and prepare a clean export.  | |||
'''Steps:'''  | |||
# Load '''Employees.csv'''  | |||
# Remove unnecessary columns  | |||
# Filter rows where '''Status''' = "Active"  | |||
# Rename columns to be presentation-ready  | |||
# Load the cleaned result into a worksheet  | |||
== Additional Exercise: Full Transformation Chain ==  | |||
'''Goal:''' Simulate a real-life workflow combining multiple steps.  | |||
'''Steps:'''  | |||
# Load both sales files  | |||
# Append them  | |||
# Add a new column to classify sales volume:  | |||
#* Low < 500  | |||
#* Medium 500–2000  | |||
#* High > 2000  | |||
# Use conditional column or custom M  | |||
# Group data by Product and Sales Level  | |||
# Output to Excel as a PivotTable  | |||
== Extension: Create a Mini-Report Using Power Pivot ==  | |||
'''Goal:''' Summarize total sales per region and volume category using Data Model.  | |||
'''Steps:'''  | |||
# Load transformed sales data to the Data Model  | |||
# Open Power Pivot → add a DAX measure for total revenue  | |||
# Create a PivotTable using:  | |||
#* Rows: Region  | |||
#* Columns: Volume Category  | |||
#* Values: Total Revenue  | |||
# Format the PivotTable for readability  | |||
----  | |||
Return to [[Power_Query_–_Basic|Main Page]]  | Return to [[Power_Query_–_Basic|Main Page]]  | ||
* [[Power Query – Introduction|Module 1: Introduction to Power Query]]  | |||
* [[Power Query – Importing and Managing Data|Module 2: Importing and Managing Data]]  | |||
* [[Power Query – Data Transformation|Module 3: Data Transformation Techniques]]  | |||
* [[Power Query – Automation and Parameters|Module 4: Automation and Parameters]]  | |||
* [[Power Query – Power Pivot Overview|Module 5: Power Pivot Overview]]  | |||
* [[Power Query – Summary and Exercises|Module 6: Summary and Final Exercises]]  | |||
Latest revision as of 09:52, 19 June 2025
Module 6: Summary and Final Exercises
Objective
Apply your Power Query skills in realistic, open-ended scenarios.
Files Used
Final Exercise 1: Combine and Analyze Sales Data
Goal: Merge January and February sales data and calculate revenue by region.
Steps:
- Load both files into Power Query: Sales_January.xlsx and Sales_February.xlsx
 - Use Home tab → Append Queries
 - Remove any unnecessary columns
 - Ensure data types are correct
 - Group by Region and sum Total Sales
 - Sort results by total revenue
 
Final Exercise 2: Filter Active Employees
Goal: Filter active employees and prepare a clean export.
Steps:
- Load Employees.csv
 - Remove unnecessary columns
 - Filter rows where Status = "Active"
 - Rename columns to be presentation-ready
 - Load the cleaned result into a worksheet
 
Additional Exercise: Full Transformation Chain
Goal: Simulate a real-life workflow combining multiple steps.
Steps:
- Load both sales files
 - Append them
 - Add a new column to classify sales volume:
- Low < 500
 - Medium 500–2000
 - High > 2000
 
 - Use conditional column or custom M
 - Group data by Product and Sales Level
 - Output to Excel as a PivotTable
 
Extension: Create a Mini-Report Using Power Pivot
Goal: Summarize total sales per region and volume category using Data Model.
Steps:
- Load transformed sales data to the Data Model
 - Open Power Pivot → add a DAX measure for total revenue
 - Create a PivotTable using:
- Rows: Region
 - Columns: Volume Category
 - Values: Total Revenue
 
 - Format the PivotTable for readability
 
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