Preppin' Data Challenge: Week 1 2023: The Data Source Bank in Power Query

Let's take a look at the requirements followed by a step-by-step:

1. Input the data: select the data file type you have from the drop down and click transform data to open Power Query

2. Split the Transaction Code to extract the letters at the start of the transaction code and rename the column 'Bank'

3. Rename the values in the Online or In-person field, Online of the 1 values and In-Person for the 2 values. 

Then repeat this step to replace 2 to In-Person

4. Change the date to be the day of the week: Click on the date column and change the date to Name of Day.

5. Different levels of detail are required in the outputs. You will need to sum up the values of the transactions in three ways:

• 1. Total Values of Transactions by each bank
• 2. Total Values by Bank, Day of the Week and Type of Transaction (Online or In-Person)
• 3. Total Values by Bank and Customer Code

In order to have multiple separate outputs we need to make a reference from the initial dataset.

In order to aggregate the Value at the different levels of detail we need to use the Group by function on Power BI.

• Total Values of Transactions by each bank

• Total Values by Bank, Day of the Week and Type of Transaction (Online or In-Person)

• Total Values by Bank and Customer Code

Output each data file and you're done!