Microsoft PL-300 (Power BI)

Model Data & Relationships

38 practice questions with explanations — 15 free to try

PassNova has 38 Microsoft PL-300 (Power BI) practice questions on Model Data & Relationships, each with a clear explanation. A 15-question taster is free with no sign-up; the full bank is part of PassNova Premium. Updated for 2026.

Sample questions

Model Data & Relationships: example questions & answers

3 worked examples with answers and explanations below. Try 15 Microsoft PL-300 (Power BI) questions free in the browser; the full 38-question Model Data & Relationships bank is part of PassNova Premium.

  1. In a star schema, which statement best describes a dimension table?

    • AIt stores the numeric measures and the foreign keys recorded at the grain of each individual business event
    • BIt stores descriptive attributes used to filter and group facts, with a unique key
    • CIt is always larger than the related fact table because it stores one row for every transaction
    • DIt must use a composite key built from all of its columns to guarantee row uniqueness

    Answer: Dimension tables hold descriptive attributes (e.g. Product, Date, Customer) with a unique key used to slice and group the numeric values stored in fact tables.

  2. Two tables are related on a key where the dimension side has unique values and the fact side has many repeats. What cardinality does Power BI assign?

    • AMany-to-many
    • BOne-to-one
    • COne-to-many
    • DMany-to-one only when sorted

    Answer: A unique key on the dimension and repeated values on the fact produces a one-to-many (1:*) relationship, the standard pattern in a star schema.

  3. By default, in what direction does filtering flow across a one-to-many relationship in Power BI?

    • AFrom the many side of the relationship back to the one side
    • BFrom the one side to the many side
    • CIn both directions automatically
    • DNo filtering occurs until cross-filter is enabled

    Answer: The default single cross-filter direction flows from the 'one' (dimension) side to the 'many' (fact) side, so dimension selections filter the related facts.

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