EXERCISE TOPIC▼
POWER BI EXERCISES▼
POWER BI EXERCISES▼
- Basic reports (10)
- Data sources (2)
- Query editor (8)
- Multiple tables (1)
- Filtering data (9)
- Drill-through filtering (1)
- Bookmarks (4)
- Charts (10)
- Other types of visualisation (1)
- Overview of maps (6)
- Calculated columns (7)
- Introduction to DAX (3)
- Creating measures in DAX (1)
- Calendars (2)
- Date functions (2)
- Roles and security (1)
- Advanced data models (4)
- Drill-through and bookmarks (3)
- Custom visuals (3)
- Parameters (5)
- Quick measures (3)
- Report themes (2)
- Power BI mobile (1)
- Power BI Templates (1)
- Tooltips (2)
Power BI | Filtering data exercise | Filter a list of popular websites and apply a slicer
This exercise is provided to allow potential course delegates to choose the correct Wise Owl Microsoft training course, and may not be reproduced in whole or in part in any format without the prior written consent of Wise Owl.
You can learn how to do this exercise if you attend one of more of the courses listed below!
| Software ==> | Power BI (92 exercises) |
| Version ==> | Latest update |
| Topic ==> | Filtering data (9 exercises) |
| Level ==> | Relatively easy |
| Classroom ==> | Introduction to Power BI / Fast track Power BI and DAX / Fast track Power BI |
| Online ==> | Introduction to Power BI / Fast track Power BI and DAX / Fast track Power BI |
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Open the Power BI report in the above folder - it contains a list of the most popular websites in the world as of the start of 2019 (ish).
Apply a filter to your matrix so that it misses out any categories containing the text porn (this is a family-oriented course, after all).
The number of sites should fall from 69 (the number shown in the default Wikipedia dataset) to 63.
Create a slicer allowing someone to choose a continent:
What you should see if you choose Europe.
Curious to know which those 8 Internet services and products sites are for Europe? Right-click on the number 8 to find out:
You may be disappointed by the Europeanness of the sites when you see the underlying data ...
Save this report as Filtered list, then close it down.