Power Query Editor

Amit Soni Jan 19 2021 · 1 min read
Share this

Assignment - 3 


Objective – Power BI Desktop, Cloud Service and End to End Workflow
Use Case – Import list of the richest people using Query Editor
Source – Richest people
Analytics – The raw data - your task is to transform it into something more presentable. Report/Dashboard – Richest people

• Create a new Power BI report, and load in the data
•Some columns have been renamed, while each person's wealth (in billions of dollars) has been extracted
1. Replace the word billion with an empty string.
2. Replace the $ symbol with an empty string.
3. Convert the resulting column to a whole number.
• Create a chart just to prove that the billions really are being treated as numbers.

Result - Transform data using Query Editor

Assignment - 4 


Objective – Power BI Desktop, Cloud Service and End to End Workflow
Use Case – Working with Date & Delimiter
Source – GOT
Analytics – The raw data - your task is to transform it into something more presentable. Report/Dashboard – GOT
• Split the author column in two and replace the resulting nulls with blanks.
• The dates needs to be format as I am not happy they are appearing.
• You should also filter the data to show only episodes directed by Daniel.
• Should show how many people watched each episode Written by the various authors o Episode Name o No. of viewers o Mostly watch Directors
• Can you show me some interesting insights in terms of the release dates that will help me to have an idea about frequency of each episode coming up and help me to plan the future production. Result - Transform data using Query Editor.

Assignment - 5
Objective – Power BI Desktop, Cloud Service and End to End Workflow
Use Case – Conditional Formatting
Source – LTD Sales
Analytics – Format as per the condition
Report/Dashboard – Sales Range
• Need to showcase the Revenue as per the State.
• Create a new column as per following condition as per the sales
1. Sales Range
2. Less 100
3. 1001 to 5000
4. 6000 to 10000
5. 11000 to 15000
6. 16000 to 20000
7. 21000 to 25000
8. Above 25000
• Create a new column as per following condition as per the Product Category where for:-
1. Furniture it should show “Office Infra”
2. Others it should show “Non-Office Infra”
Result - Transform data using Query Editor

Comments
Read next