WISE OWL EXERCISES
POWER BI EXERCISES
- PowerPivot data models (7)
- Pivot tables using PowerPivot (2)
- Using Excel tables (3)
- Using other data sources (1)
- Transforming data (Power Query) (7)
- Calculated columns (7)
- Measures (2)
- The CALCULATE function (15)
- More advanced DAX functions (5)
- Calendars (1)
- Date functions (10)
- Hierarchies (2)
- KPIs (5)
- Power View (4)
- Power BI Desktop overview (3)
- Power BI Desktop maps (1)
PowerPivot | Transforming data (Power Query) exercise | Import financial data, and split it into different columns
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.
The answer to the exercise will be included and explained if you attend the course listed below!
You need a minimum screen resolution of about 700 pixels width to see our exercises. This is because they contain diagrams and tables which would not be viewable easily on a mobile phone or small laptop. Please use a larger tablet, notebook or desktop computer, or change your screen resolution settings.
In a new workbook, use Power Query to load data from the Exchange Rates table in the Tables workbook:
Initially the data looks like this.
Load this into a PowerPivot data model, splitting the currencies:
As a bonus task, filter the data to exclude the (pointless) GBP to GBP exchange rate.
Too easy? Load data from the Share Prices worksheet in the Tables workbook:
The investment symbol needs splitting out, and the price should be numeric.
Split the investment into the name and code, and make the price into a number, to get something like this:
Investments sorted by the Change column, with the highest value first. You should filter the table in Power Query to omit any investments whose prices contain $ or € symbols. You can type in a € by pressing Alt + Ctrl + 4.
Save this workbook as Splitting Shares, then close it down.