Exam PL-300 topic 1 question 52 discussion

Actual exam question from Microsoft's PL-300

Question #: 52
Topic #: 1

You have a Power BI report named Report that contains the following tables.

For the last three days, refresh in Power BI has failed, and you receive the following error message: “You have reached the maximum allowable memory allocation for your tier. Consider upgrading to a tier with more available memory.”

You need to resolve the error and ensure that query response times are minimized for end users.

What should you do?

A. Merge the Sales person and invoice tables based on the SalesPersonId column.
B. Change the invoice table to a DirectQuery table and read the data live from the source, retaining only the dimension tables as import tables.
C. Reduce the size of the invoice table by summarizing sales by Product, Sales person, Calendar, and Customer.
D. Change the invoice table to a composite table that contains historical data as a DirectQuery table and hot data as an import table, and then partition the table.

Show Suggested Answer

Suggested Answer: D 🗳️

by kay000001 at June 17, 2025, 1:40 a.m.

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PhoebeZ

3 weeks, 2 days ago

Selected Answer: C

here is what Gemini says: The feature in Option D is designed for fact tables that have a long history of data (e.g., many years of transactions). It works by partitioning the table so that recent, "hot" data is imported for fast performance, while older, "cold" data is left in DirectQuery mode to save memory. The problem in the question states that the Invoice table already only contains data from the "last three months." There is no older, historical data to partition off into DirectQuery mode. The entire 12-million-row table is considered "hot" data. Therefore, since the recent data itself is too large, the correct solution is C (summarizing the data). This directly reduces the number of rows within that three-month period, which solves the memory issue.

upvoted 3 times

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Lulu_2022

1 month ago

Selected Answer: D

- Keeps “hot” recent data (e.g. last 30 days) fast with import mode - Pushes bulk historical data (e.g. older than 6 months) to DirectQuery - Memory load drops, and the most viewed data stays performant - Partitioning lets you manage refresh logic smartly and incrementally

upvoted 4 times

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