PL-300 Prepare the data Practice Question
You are a data analyst at a utility company. You load a table of meter readings into Power BI Desktop from an Azure SQL Database. The table has columns MeterId, ReadingTimestamp, and Consumption. You discover duplicate rows caused by a known upstream issue where the same reading is sometimes inserted twice with identical values in all three columns. You need to remove these exact duplicate rows in Power Query while keeping one copy of each reading. What should you do?
⚠ Common exam trap
The trap here is choosing a single column as the duplicate key, which feels efficient but actually removes valid readings that share the same meter identifier.
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
✓
Select all three columns, then use Remove Rows > Remove Duplicates.
Remove Duplicates treats the set of selected columns as the key for comparison. Selecting MeterId, ReadingTimestamp, and Consumption means only rows identical across all three are collapsed, which matches the described upstream duplication. Narrower keys would delete valid readings, and an index column would prevent any matches.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add an index column, then use Remove Rows > Remove Duplicates on the index column.
Why it's wrong here
An index column contains unique values for every row, so no two rows would ever be considered duplicates. This approach would remove nothing at all. The index column is useful for other purposes, such as creating a stable sort key, but it cannot identify the duplicate readings described here.
- ✗
Group By MeterId, ReadingTimestamp, and Consumption with an All Rows operation, then expand the first row of each group.
Why it's wrong here
Grouping with All Rows and expanding one row per group can emulate deduplication, but it is unnecessarily complex and can change column order or types during expansion. Remove Duplicates on the same three columns achieves the same result more directly and with less risk of introducing transformation errors during the expand step.
- ✗
Select the MeterId column only, then use Remove Rows > Remove Duplicates.
Why it's wrong here
Removing duplicates based only on MeterId would keep a single row per meter and discard all other legitimate readings for that meter. That would destroy nearly all the data. The duplicate definition in this scenario requires all three columns to match, so a single-column key is far too aggressive.
- ✓
Select all three columns, then use Remove Rows > Remove Duplicates.
Why this is correct
Remove Duplicates evaluates the selected columns as a composite key, so rows that match on MeterId, ReadingTimestamp, and Consumption are treated as duplicates. One copy of each distinct combination is retained. This precisely targets the exact duplicates described without risking removal of legitimate readings that differ in any column.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This PL-300 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PL-300 exam.