PL-300 Prepare the data Practice Question
You are merging two queries in Power Query: 'Orders' and 'Customers'. The 'Orders' table has a 'CustomerID' column, and 'Customers' has 'CustomerID' and 'Name'. You need to bring the 'Name' into 'Orders' but only for matching CustomerIDs; unmatched rows should be removed. Which join kind should you use?
⚠ Common exam trap
Test-takers frequently confuse Left Outer join with Inner join, thinking that 'bringing in data only for matches' means keeping all left rows, but Left Outer retains unmatched left rows with nulls, while Inner removes them entirely.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Inner
The Inner join kind in Power Query returns only rows where there is a match in both tables based on the key columns. Since the requirement is to bring the 'Name' into 'Orders' only for matching CustomerIDs and to remove unmatched rows, the Inner join is the correct choice. It ensures that only orders with a corresponding customer in the 'Customers' table are retained, and the 'Name' column is added to those matching rows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Right Anti
Why it's wrong here
Right Anti join in Power Query returns all rows from the right table (Customers) that have no corresponding match in the left table (Orders). Choosing this would produce only customers without any orders, completely excluding all order-related data, which defeats the purpose of merging the two queries for order analysis.
- ✗
Full Outer
Why it's wrong here
Full Outer join combines every row from both Orders and Customers, aligning matches and filling nulls where either side lacks a pairing, thus preserving all records. While comprehensive, this yields a wide result set with many null columns for unmatched orders or customers, introducing noise rather than the clean, matched dataset typically needed for analyzing order-customer relationships.
- ✓
Inner
Why this is correct
Inner join retains only rows where a matching key exists in both tables—so an order is included only if it has a corresponding customer, and customers appear only if they have at least one order. This produces exactly the intersection of the two queries, which is the standard approach for combining transactional and dimensional data to analyze completed order-customer pairs.
- ✗
Left Outer
Why it's wrong here
Left Outer join preserves every row from the Orders table and brings in matching Customer fields only when available, leaving nulls for orders without a valid customer. Using this would retain unmatched orders in the result, which may be undesirable if the analysis requires complete customer information for every order record; it also fails to exclude orders that have no customer association.
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