Microsoft Power BI PL-300 Practice Test (Data Analyst)

PL-300 practice test: what's covered

• Microsoft Power BI
• Prepare
• Model
• Visualize & Analyze
• Deploy & Maintain

Free PL-300 sample questions

1. You import a 200-million-row sales fact table into Power BI Desktop. The report only ever shows the last 13 months, but refreshes are slow and the .pbix file is huge. You want to reduce model size and refresh time WITHOUT changing the visuals. What is the BEST first step in Power Query?

   • A. Filter rows in Power Query to keep only the last 13 months before loading
   • B. Load all rows, then hide the older rows in the report view
   • C. Switch the table to DirectQuery so nothing is imported
   • D. Increase the data refresh timeout in the dataset settings
   Show answer

   Correct: A. Filtering at the Power Query (query-folding) stage removes the rows before they hit the model, shrinking the file and refresh time and ideally folding the filter back to the source. Hiding rows in the report (B trap) still imports and stores every row — no size benefit. Switching to DirectQuery changes the architecture and visual behaviour. Raising the timeout treats the symptom, not the volume.

2. A column named SalesDate arrives from a CSV as the Text data type in the format "2025-03-14". Time-intelligence DAX later fails because the model has no proper date column. What should you do in Power Query to fix the ROOT cause?

   • A. Change the column data type to Date (using Locale if needed)
   • B. Create a DAX calculated column with FORMAT(SalesDate, "Date")
   • C. Sort the column ascending so it is recognised as a date
   • D. Mark the table as a date table in the model view
   Show answer

   Correct: A. The text needs to be converted to a real Date type in Power Query (Change Type, with "Using Locale" if the regional format differs) so the engine treats it as a date. FORMAT (B trap) returns TEXT, which still cannot drive time intelligence and bloats the model. Sorting does not change the type. Marking a date table is a later modelling step that requires a date column to already exist.

3. You have 12 monthly CSV files with IDENTICAL columns (Jan.csv … Dec.csv) sitting in one folder, and a 13th file arrives every month. You want one combined table that automatically picks up new files on each refresh. Which approach is BEST?

   • A. Use Get Data > Folder, then Combine Files (which builds a sample-file transform function)
   • B. Import each CSV separately and use Merge Queries to join them
   • C. Import each CSV and copy-paste the rows into a single sheet
   • D. Use Append on the first 12 queries and re-do it each month
   Show answer

   Correct: A. Get Data > Folder + Combine Files generates a helper function applied to every file in the folder, so new files are picked up automatically on refresh — perfect for same-schema files. Merge (B trap) joins tables side-by-side on a key (adds columns), not stacks rows; you want to stack rows. Manual paste and a fixed 12-query Append are not refresh-friendly and break when the 13th file lands.

4. Two tables — Customers (CustomerID, Name) and Orders (OrderID, CustomerID, Amount) — must be combined so that each order row also shows the customer Name. In Power Query, which operation produces the correct result?

   • A. Merge Queries on CustomerID, then expand the Name column
   • B. Append Queries to stack both tables on top of each other
   • C. Group By CustomerID on the Orders table
   • D. Pivot the CustomerID column in the Orders table
   Show answer

   Correct: A. Merge is a join: it matches rows on a key (CustomerID) and lets you expand columns from the other table — exactly what is needed to add Name to each order. Append (B trap) stacks rows vertically and only makes sense for same-schema tables, not for adding a lookup column. Group By aggregates, and Pivot reshapes columns — neither performs a join.

5. During Column Profiling you notice the Column Quality bar shows 4% Error and 2% Empty for a numeric Quantity column. You must investigate the bad values before deciding how to handle them. What is the FASTEST way to see only the offending rows?

   • A. Right-click the column and choose Keep Errors to isolate the error rows
   • B. Choose Remove Errors immediately so the report is clean
   • C. Replace the errors with 0 and continue
   • D. Change the column type to Text so the errors disappear
   Show answer

   Correct: A. Keep Errors filters the query down to ONLY the rows that errored so you can inspect the source values and decide the right fix. Remove Errors (B trap) deletes them before you understand why they failed — you lose the evidence. Replacing with 0 silently corrupts aggregates. Changing the type to Text hides, but does not resolve, the underlying conversion problem.

Last updated: 2026-10-19

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