Power Query – Summary and Exercises: Difference between revisions
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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]] | ||
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
Return to Main Page