PL-300 Visualize and analyze the data Practice Question
You have a Power BI dataset with a large fact table. You need to optimize report performance when users filter by date. What should you do?
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
✓
Mark the date table as a date table in Power BI.
Marking a date table as a date table enables time intelligence functions and better performance. Option B is wrong because hiding columns does not improve performance. Option C is wrong because disabling cross-filtering might affect user experience but not performance directly. Option D is wrong because summarizing the fact table reduces granularity, which may not be desired.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Mark the date table as a date table in Power BI.
Why this is correct
Marking a table as a date table in Power BI assigns a calendar semantic to a dedicated date column, which enables the VertiPaq query engine to natively optimize time-intelligence calculations such as YTD, QTD, and same-period comparisons. The engine uses the contiguous date range of the marked table to generate efficient filter predicates, avoiding fallback to the auto date/time hidden tables and reducing the overhead of date range evaluation.
- ✗
Hide all columns except the date column.
Why it's wrong here
Hiding columns in the Fields pane only affects the user interface and does nothing to alter the data model or the physical query plan. Hidden columns are still loaded into memory, still participate in relationships, and still contribute to dictionary encoding and scan costs when referenced by a measure or row-level security rule. Consequently, this action has zero measurable impact on storage engine performance while making the model less discoverable.
- ✗
Disable cross-filtering between tables.
Why it's wrong here
Cross-filtering direction controls how filters flow between related tables in a visual and is executed in the relationship engine layer after storage engine hits are returned; it is a query behavior, not a storage or compression mechanism. Setting cross-filtering to None may cause required filter propagation to fail, leading to empty or over-aggregated visuals, but it does not reduce the rows scanned or the memory footprint of the fact table. Therefore it cannot improve query performance and may actually degrade analytical correctness.
- ✗
Summarize the fact table by month.
Why it's wrong here
Pre-aggregating the fact table to a monthly grain can reduce row counts, but it irreversibly discards day-level and transaction-level detail, which corrupts any measure that relies on exact dates, time between events, or drill-through to line-level data. Even when performance would improve, that benefit only materializes after building a properly maintained aggregation table or using composite models; naively replacing the fact table with a monthly summary creates incorrect results for time-intelligence calculations and parent-child hierarchies. This is a modeling decision made for specific business requirements, not a general-purpose performance tuning technique.
Go deeper
Related to this question
About these practice questions
This PL-300 question is part of Courseiva's 217-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.