Header promotion in Power BI - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

What does header promotion do in Power Query?

In Power Query, what is the main effect of using the 'Use First Row as Headers' feature?

A It sorts the data based on the first row values.

B It deletes the first row of data permanently.

C It duplicates the first row and adds it as a new column.

D It converts the first row of data into column headers.

💡 Hint

Think about how the table's columns get their names.

Header promotion changes the first row of data into the column headers, making the data easier to understand and work with.

❓ dax_lod_result

intermediate

DAX measure after header promotion

After promoting headers in Power Query, you load a table named 'SalesData' with columns: 'Product', 'Region', and 'Sales'. You create this DAX measure:

Total Sales = SUM(SalesData[Sales])

What will be the result of Total Sales if the 'Sales' column contains values 100, 200, and 300?

A Error: Column 'Sales' not found

B 600

C 0

D 100

💡 Hint

Check if the column name matches exactly after header promotion.

Promoting headers ensures the column is named 'Sales'. The SUM adds 100 + 200 + 300 = 600.

🔧 Formula Fix

advanced

Why does this header promotion step fail?

You have a table where the first row contains mixed data types. You apply 'Use First Row as Headers' but get an error. What is the most likely cause?

A The first row has duplicate values causing invalid column names.

B The first row contains null values which cannot be headers.

C The table has more than 1000 rows, which is unsupported.

D The data source is not connected.

💡 Hint

Headers must be unique and valid.

If the first row has duplicate values, Power Query cannot create unique column headers, causing the error.

❓ visualization

advanced

Best visualization after header promotion

You have promoted headers in a sales dataset with columns: 'Date', 'Product', 'Quantity', and 'Revenue'. Which visualization best shows total revenue by product?

A Bar chart with 'Product' on X-axis and sum of 'Revenue' on Y-axis.

B Line chart with 'Date' on X-axis and 'Quantity' on Y-axis.

C Scatter plot with 'Quantity' on X-axis and 'Date' on Y-axis.

D Pie chart showing count of 'Product' entries.

💡 Hint

Think about comparing totals by category.

A bar chart with products on the X-axis and total revenue on the Y-axis clearly shows revenue comparison by product.

❓ data_modeling

expert

Impact of header promotion on data model relationships

You import two tables: 'Orders' and 'Customers'. 'Orders' has a first row with customer IDs but no headers. You promote headers in 'Orders' and the customer ID column is named 'CustomerID'. 'Customers' already has a 'CustomerID' column. What is the impact on creating a relationship between these tables?

A You cannot create a relationship because promoted headers are not recognized in the model.

B Relationships are created automatically regardless of header names.

C You can create a relationship on 'CustomerID' because headers match after promotion.

D You must rename columns manually after promotion to create relationships.

💡 Hint

Headers define column names used in relationships.

Promoting headers correctly names the column 'CustomerID', allowing you to create relationships with the 'Customers' table on that column.