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Microsoft PL-300 Date Tables Calculated Columns And Calculated Tables Practice Test

Skills 2.1 • 25 original questions

This Microsoft PL-300 Power BI Data Analyst practice test focuses on date tables calculated columns and calculated tables through original scenario-based questions aligned to the skills measured as of April 20, 2026. Use the full ExamSnap PL-300 collection for broader practice across all current skill areas. For broader exam preparation, review the Microsoft PL-300 Exam Dumps page.

Instructions: Select the best answer for each question. Review the explanation after answering; each distractor includes a reason it is not the best choice for that scenario.

Question 1

During a monthly KPI review at Proseware Services, the BI developer must provide one reusable calendar dimension for consistent date analysis and time intelligence. Which action most directly satisfies the requirement for the service-level dashboard, analysis cycle 1?

Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Create and mark a common date table that supports consistent time analysis across facts
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: D

Why: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Option review:

A: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

B: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

C: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

D: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

E: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 2

Fourth Coffee is revising its analytics solution during a regional reporting consolidation. The team needs to choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. Which Power BI action should the Power BI data analyst choose for the forecast report, analysis cycle 1?

Create and mark a common date table that supports consistent time analysis across facts
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: C

Why: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Option review:

A: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

B: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

C: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

D: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

E: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 3

A design review for the mobile report, analysis cycle 2 at Fabrikam Manufacturing identifies one required capability: provide one reusable calendar dimension for consistent date analysis and time intelligence. Which implementation is the strongest fit?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Create and mark a common date table that supports consistent time analysis across facts

Correct answer: E

Option review:

A: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

B: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

D: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

E: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 4

For the executive report, analysis cycle 2, Adventure Works wants the least indirect way to choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. Which Power BI feature or action should the data analyst select?

Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Create and mark a common date table that supports consistent time analysis across facts
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design

Correct answer: D

Option review:

A: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

B: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

C: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

D: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

E: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 5

The report author at Proseware Services is comparing several approaches for a semantic model modernization. The chosen approach must provide one reusable calendar dimension for consistent date analysis and time intelligence. Which option best meets that condition?

Create and mark a common date table that supports consistent time analysis across facts
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: A

Option review:

A: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

B: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

C: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 6

A support escalation at Fourth Coffee has been narrowed to one requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. Which configuration should be investigated first for the finance semantic model, analysis cycle 3?

Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Create and mark a common date table that supports consistent time analysis across facts
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design

Correct answer: A

Option review:

A: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

C: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

D: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 7

An analytics governance review at Fabrikam Manufacturing asks the BI developer to provide one reusable calendar dimension for consistent date analysis and time intelligence. Which action aligns most directly with that requirement?

Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Create and mark a common date table that supports consistent time analysis across facts
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Correct answer: C

Option review:

A: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

C: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

D: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

E: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 8

Before the customer report, analysis cycle 4 is released, the analytics team must choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. Which Power BI implementation should be added?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Create and mark a common date table that supports consistent time analysis across facts
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables

Correct answer: C

Option review:

A: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

B: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

D: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

E: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 9

Proseware Services is replacing a manual analytics process. The replacement must reliably provide one reusable calendar dimension for consistent date analysis and time intelligence. Which choice should be implemented for the regional workspace, analysis cycle 5?

Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Create and mark a common date table that supports consistent time analysis across facts
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: B

Option review:

B: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

C: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 10

Which Power BI action best matches this technical purpose for the inventory model, analysis cycle 5: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time.

Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Create and mark a common date table that supports consistent time analysis across facts

Correct answer: A

Why: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

Option review:

A: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

B: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

C: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

D: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

E: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 11

A runbook for the service-level dashboard, analysis cycle 6 contains this description: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. Which Power BI feature or action belongs in the runbook?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Create and mark a common date table that supports consistent time analysis across facts

Correct answer: E

Why: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

Option review:

A: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

B: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

C: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

D: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

E: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 12

During validation of the forecast report, analysis cycle 6, the analytics lead needs a capability that behaves as follows: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. Which choice is correct?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Create and mark a common date table that supports consistent time analysis across facts
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: C

Why: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

Option review:

A: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

B: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

C: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

D: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

E: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 13

A stakeholder asks why a particular Power BI feature should be used for the mobile report, analysis cycle 7. The required behavior is: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. Which action provides that behavior?

Create and mark a common date table that supports consistent time analysis across facts
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: A

Why: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

Option review:

A: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

B: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

C: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

D: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

E: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 14

The executive report, analysis cycle 7 is moving to production at Fourth Coffee. Which action should be approved when the goal is to choose a refresh-time calculated column or DAX-generated table when the result must persist in the model?

Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Create and mark a common date table that supports consistent time analysis across facts
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Correct answer: E

Option review:

C: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

E: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 15

A data analyst at Fabrikam Manufacturing must satisfy this acceptance criterion for the sales model, analysis cycle 8: provide one reusable calendar dimension for consistent date analysis and time intelligence. Which implementation is most appropriate?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Create and mark a common date table that supports consistent time analysis across facts

Correct answer: E

Option review:

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 16

A self-service analytics rollout at Adventure Works can proceed only after the team can choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. What should the data analyst configure?

Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Create and mark a common date table that supports consistent time analysis across facts
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: B

Option review:

A: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

B: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

C: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

E: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 17

The analytics team at Proseware Services has ruled out unrelated redesign work. Which action directly enables the team to provide one reusable calendar dimension for consistent date analysis and time intelligence for the operations dashboard, analysis cycle 9?

Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Create and mark a common date table that supports consistent time analysis across facts
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design

Correct answer: B

Option review:

C: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

D: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

E: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 18

An audit finding for the customer report, analysis cycle 9 says the current design cannot choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. Which Power BI action most directly closes the gap?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Create and mark a common date table that supports consistent time analysis across facts

Correct answer: B

Option review:

A: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

C: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

E: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 19

For the regional workspace, analysis cycle 10, the BI developer needs a repeatable solution that will provide one reusable calendar dimension for consistent date analysis and time intelligence. Which option should replace the current ad hoc process?

Create and mark a common date table that supports consistent time analysis across facts
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Correct answer: A

Option review:

B: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

C: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 20

During a customer analytics initiative, Adventure Works defines the desired outcome as follows: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. Which Power BI capability should the team use?

Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Create and mark a common date table that supports consistent time analysis across facts
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Correct answer: E

Option review:

C: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 21

A new requirement is added to the service-level dashboard, analysis cycle 11: provide one reusable calendar dimension for consistent date analysis and time intelligence. Which action should the self-service BI administrator take?

Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Create and mark a common date table that supports consistent time analysis across facts
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design

Correct answer: D

Option review:

E: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 22

Fourth Coffee is troubleshooting an unexpected reporting result. The decisive requirement is to choose a refresh-time calculated column or DAX-generated table when the result must persist in the model. Which feature or configuration is most relevant?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Create and mark a common date table that supports consistent time analysis across facts

Correct answer: C

Option review:

A: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

B: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

E: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: choose a refresh-time calculated column or DAX-generated table when the result must persist in the model.

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 23

A technical workshop for the mobile report, analysis cycle 12 documents this behavior: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. Which Power BI choice is being described?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Create and mark a common date table that supports consistent time analysis across facts
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables

Correct answer: C

Why: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

Option review:

A: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

B: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

C: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. This directly addresses the stated requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

D: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

E: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering..

Learning point: Create and mark a common date table that supports consistent time analysis across facts

Question 24

The analytics lead must identify the Power BI capability that provides this function: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. Which answer is correct for the executive report, analysis cycle 12?

Create and mark a common date table that supports consistent time analysis across facts
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility

Correct answer: C

Why: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

Option review:

A: A dedicated date dimension provides complete calendar attributes and a consistent basis for DAX time intelligence and report filtering. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

B: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

C: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time. This directly addresses the stated requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

D: A role-playing dimension represents the same business dimension in more than one analytical role and must be modeled so each role is unambiguous. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

E: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Calculated columns and tables are computed during refresh and stored in the model, unlike measures that evaluate at query time..

Learning point: Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required

Question 25

A modernization plan for the sales model, analysis cycle 13 requires the team to provide one reusable calendar dimension for consistent date analysis and time intelligence. Which Power BI action is the clearest fit?

Reuse one dimension in multiple relationship roles, such as order date and ship date, with an appropriate role-playing design
Create and mark a common date table that supports consistent time analysis across facts
Use calculated columns for row-level stored results and calculated tables when a DAX-generated table is required
Configure table and column properties such as names, descriptions, data categories, summarization, and visibility
Set relationship cardinality and cross-filter direction to match the grain and filtering behavior of the tables

Correct answer: B

Option review:

D: Well-configured model metadata improves report authoring, default aggregation behavior, discoverability, and the consumer experience. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

E: Cardinality describes uniqueness on each side of a relationship, while cross-filter direction controls how filters propagate through the model. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: provide one reusable calendar dimension for consistent date analysis and time intelligence.

Learning point: Create and mark a common date table that supports consistent time analysis across facts

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